Cubic SVM neural classification algorithm for Self-excited Acoustical System

Lalik, Krzysztof; Kozek, Mateusz

doi:10.1109/msm49833.2020.9201724

Cited by 5 publications

(2 citation statements)

References 17 publications

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“…One of the biggest is the frequency jump and limit cycle change described in [25]. One method to analyze such frequency spectra is to use classification methods [36]. Nevertheless, it is more advantageous to implement active filters in a positive feedback loop.…”

Section: Introductionmentioning

confidence: 99%

Non-Destructive Acoustical Rock Bolt Testing System with Intelligent Filtering in Salt Mine ‘Wieliczka’

et al. 2021

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This article presents the application of a self-excited acoustic SAS system for non-destructive testing (NDT) for roof-bolt housings in laboratory and real mine conditions. The proposed system with a filtering mechanism was applied to the J64-27 composite anchors. The conducted tests allowed successful confirmation of the usefulness of the system in the detection of rod defects, damage of the mechanism coupling the anchor to the rock mass and testing of the stress state of the anchor itself. The proposed filtering system allowed eliminating the effect of jump change of frequency in the limit cycle of self-excited system. The proposed method is a novel solution for safety diagnostics of bolt housings in mining applications.

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Section: Introductionmentioning

confidence: 99%

Non-Destructive Acoustical Rock Bolt Testing System with Intelligent Filtering in Salt Mine ‘Wieliczka’

et al. 2021

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“…Applications of fuzzy systems in predicting the spread of pandemics are also known [8]- [11]. In addition, fuzzy logic and neural networks allow the regulation of traffic in many industrial manufacturing plants [12]- [15]. However, this paper presents an intelligent biometric platform that uses artificial intelligence to supervise and search for individuals with suspected COVID infection.…”

Section: Introductionmentioning

confidence: 99%

Convolutional mask-wearing recognition algorithm for an interactive smart biometric platform

Bałazy¹,

Gut²,

Knap³

2021

Robot. syst., appl.

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This paper presents the results of a neural convolutional system for recognizing the wearing of a mask by people entering a building. The algorithm is provided with input data thanks to cameras placed in the humanoid robot COVIDguard. The data collected by the humanoid -the temperature of people entering the facility, the location of the person, the way the protective mask was applied -are stored in the cloud, which enables the application of advanced image recognition algorithms and, consequently, the tracking of people within the range of the robot's sensory systems by the administrator and the verification of the security level in the given premises. The paper presents the architecture of the intelligent COVIDguard platform, the structure of the sensory system and the results of the neural network learning.

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Deep Learning Damage Forecasting for Rotating Devices Using Bayesian Sub-predictors

Knap,

Bałazy,

Podlasek

2024

Lecture Notes in Networks and Systems

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Cubic SVM neural classification algorithm for Self-excited Acoustical System

Cited by 5 publications

References 17 publications

Non-Destructive Acoustical Rock Bolt Testing System with Intelligent Filtering in Salt Mine ‘Wieliczka’

Non-Destructive Acoustical Rock Bolt Testing System with Intelligent Filtering in Salt Mine ‘Wieliczka’

Convolutional mask-wearing recognition algorithm for an interactive smart biometric platform

Deep Learning Damage Forecasting for Rotating Devices Using Bayesian Sub-predictors

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