Statistical analysis of cavitation erosion impacts in a vibratory apparatus with copulas

Taillon, Gabriel; Onishi, Keisuke; Mineshima, T.; Miyagawa, Kazuyoshi

doi:10.1088/1755-1315/240/6/062035

Cited by 5 publications

(4 citation statements)

References 11 publications

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“…Also, the p-values of the current 1 to 3 are below 0.82. The above indicated that there is no statistical significance and the R 2 does not describe properly the linear model proposed (Bolaños 2018;Taillon et al 2019;Bolaños and Botero 2021). An alternative to describe this phenomenon is a non-linear adjustment using copula analyses.…”

Section: Resultsmentioning

confidence: 93%

“…If H(x,y) is a joint distribution function of two continuous variables, then a copula C can be defined that relates the marginal distributions F and G of the random variables x and y in the way shown in Eq. 1 and for the case where the variables are independent, it can be modeled using the copula C(x,y)=xy (Taillon et al 2019). F(x) and G(y) are the marginal distributions for each of the physical variables and in this case a hydraulic variable and an electrical variable.…”

Section: Couple Analysismentioning

confidence: 99%

“…A nonlinear multivariate adjustment methodology is applied through copulas, whose application is not so frequent in the study of turbomachines and has scarce exploration regarding the relationship between electrical variables and hydraulic variables. Taillon et al (2019) developed a method of analysis of cavitation peaks (impact events) using copulas. Impact events, also known as spikes, are defined as maximums in the amplitude pressure applied to the surface of a material.…”

Section: Introductionmentioning

confidence: 99%

“…The measured parameters show that they are not independent but have a complex and asymmetric dependency structure. The copula is a better fit compared to a joint distribution of independent marginals (Taillon et al 2019).…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Experimental-Modeling Evaluation Between Hydraulic and Electrical Variables Using Copulas and Spectral Analysis for a Centrifugal Pump

2023

JAFM

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Centrifugal pumps are turbomachines that have wide industrial applications and could perform in different ways such as pump and turbine mode. The maintenance of this equipment is mostly carried out using invasive methods that are expensive, time-consuming, and even complicated. The application of non-invasive methods is sought since they offer the advantage of real-time monitoring without stopping the process, reducing component assembly and disassembly times and providing a faster response. The aim of this work is done an experimental investigation that shows evidence about how the information on the hydraulic variables can be obtained if the electrical variables are monitored for the modes of operation such as pump and turbine. This work is divided into two parts, the first part is based on a statistical analysis to perform a multivariate adjustment through copulas and probability distributions. The second part focuses on the graphical analysis of the power density spectra for the hydraulic variables, the torque, and the defined electrical variables. The amplitude peaks of each variable and which peaks are common between them are determined. A statistically significant fit for Tawn type 2 copula is obtained with the indicator variable of pressure fluctuation and a multivariate transformation of the three-phase network currents. In the spectra analysis, common amplitude peaks are observed between the spectra that indicate the information flow on the phenomena between the hydraulic variables and the electrical variables.

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Section: Resultsmentioning

confidence: 93%

Section: Couple Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Experimental-Modeling Evaluation Between Hydraulic and Electrical Variables Using Copulas and Spectral Analysis for a Centrifugal Pump

2023

JAFM

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Linear and copula model for understanding climate drivers of hydroclimatic extremes: a case study of Serayu river basin, Indonesia

2023

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Spatial modeling sensitivity analysis: Copula selection for wind speed dependence

Shahirinia,

Farahmandfar,

Bina

et al. 2024

AIP Advances

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As the adoption of wind energy as a key renewable energy source accelerates, precise power flow analysis becomes crucial for accurate power delivery forecasting. This paper addresses the inherent uncertainties in wind speed data at different wind farm locations by conducting a sensitivity analysis to assess wind farm pairs. The analysis accommodates various data sizes, namely, short, medium, and large, and diverse spatial relationships between wind farms. By leveraging National Renewable Energy Laboratory wind speed data from nine distinct wind farms, the dependence structure between wind farm pairs is modeled using copulas. This modeling takes both the wind speed knowledge level and the various spatial interplays among the wind farm pairs into consideration. The findings indicate an inverse proportionality between the strength of dependence and the distance separating the wind farm pairs.

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Statistical analysis of cavitation erosion impacts in a vibratory apparatus with copulas

Cited by 5 publications

References 11 publications

Experimental-Modeling Evaluation Between Hydraulic and Electrical Variables Using Copulas and Spectral Analysis for a Centrifugal Pump

Experimental-Modeling Evaluation Between Hydraulic and Electrical Variables Using Copulas and Spectral Analysis for a Centrifugal Pump

Linear and copula model for understanding climate drivers of hydroclimatic extremes: a case study of Serayu river basin, Indonesia

Spatial modeling sensitivity analysis: Copula selection for wind speed dependence

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