scholarly journals Experimental Analysis of Dynamic Interaction Between a Centrifugal Compressor and its Casing

2014 ◽  
Author(s):  
P. Almeida ◽  
C. Gibert ◽  
F. Thouverez ◽  
X. Leblanc ◽  
J.-P. Ousty
Keyword(s):  
Centrifugal Compressor ◽  
Time Series Data ◽  
Laser Doppler Vibrometer ◽  
Series Data ◽  
Physical Parameters ◽  
Full Spectrum ◽  
Scanning Laser Doppler Vibrometer ◽  
Recorded Data ◽  
Interaction Experiment ◽  
Run Up

In turbomachinery, one way to improve aerodynamic performance and reduce fuel consumption consists of minimizing the clearance between rotor and casing. Yet the probability of contact is increased and this may lead in some specific conditions to a large and even unstable excitation on the impeller and stator. To achieve better understanding of the dynamic behavior occurring during the blade-to-casing contact, many numerical studies have been conducted but only a few experiments have been reported in the literature thus far. The interaction experiment reported in this paper involves a low-pressure, rotating centrifugal compressor and its casing tested in a vacuum chamber. Contact is initiated by introducing a gap near zero, and certain events with significant dynamic levels are observed during the run-up. Measurements are performed using strain gauges on both the rotating and stationary parts and a Scanning Laser Doppler Vibrometer on the stator. This research focuses on an analysis of the recorded data. Time series data are also analyzed by means of standard signal processing and a full spectrum analysis in order to identify the direction of traveling wave propagation on the two structures as well as nodal diameters and frequencies. The dynamic response of structures is accompanied by variations in other physical parameters such as temperature, static deformed shapes, speed and torque. A wearing pattern is evaluated following the contact experiments. The spectral content of response is dominated by frequency modes excited by engine orders as well as by sidebands due to inherent system non-linearity.

scholarly journals Experimental Analysis of Dynamic Interaction Between a Centrifugal Compressor and Its Casing

2014 ◽  
Vol 137 (3) ◽  
Author(s):  
P. Almeida ◽  
C. Gibert ◽  
F. Thouverez ◽  
X. Leblanc ◽  
J.-P. Ousty
Keyword(s):  
Centrifugal Compressor ◽  
Time Series Data ◽  
Laser Doppler Vibrometer ◽  
Series Data ◽  
Physical Parameters ◽  
Full Spectrum ◽  
Rotating Speed ◽  
Scanning Laser Doppler Vibrometer ◽  
System Nonlinearity ◽  
Run Up

In turbomachinery, one way to improve aerodynamic performance and reduce fuel consumption consists of minimizing the clearance between rotor and casing. Yet, the probability of contact is increased and this may lead in some specific conditions to a large and even unstable excitation on the impeller and stator. To achieve better understanding of the dynamic behavior occurring during the blade-to-casing contact, many numerical studies have been conducted but only a few experiments have been reported in the literature thus far. The interaction experiment reported in this paper involves a low-pressure, rotating centrifugal compressor and its casing tested in a vacuum chamber. Contact is initiated by introducing a gap near zero, and certain events with significant dynamic levels are observed during the run-up. Measurements are performed using strain gauges on both the rotating and stationary parts and a scanning laser Doppler vibrometer on the stator. This research focuses on an analysis of the recorded data. Time series data are also analyzed by means of standard signal processing and a full spectrum analysis in order to identify the direction of traveling wave propagation on the two structures as well as nodal diameters and frequencies. The dynamic response of structures is accompanied by variations in other physical parameters such as temperature, static deformed shapes, speed, and torque. A wearing pattern is evaluated following the contact experiments. The spectral content of response is dominated by frequency modes excited by rotating speed harmonics as well as by sidebands due to inherent system nonlinearity.

scholarly journals X-ray Flux and Spectral Variability of the TeV Blazars Mrk 421 and PKS 2155-304

Galaxies ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 64
Author(s):  
Alok C. Gupta
Keyword(s):  
Black Hole ◽  
Time Series Data ◽  
Series Data ◽  
Physical Parameters ◽  
Electromagnetic Spectrum ◽  
Black Hole Mass ◽  
Spectral Variability ◽  
Massive Black Hole ◽  
X Ray ◽  
Northern And Southern Hemispheres

We reviewed X-ray flux and spectral variability properties studied to date by various X-ray satellites for Mrk 421 and PKS 2155-304, which are TeV emitting blazars. Mrk 421 and PKS 2155-304 are the most X-ray luminous blazars in the northern and southern hemispheres, respectively. Blazars show flux and spectral variabilities in the complete electromagnetic spectrum on diverse timescales ranging from a few minutes to hours, days, weeks, months and even several years. The flux and spectral variability on different timescales can be used to constrain the size of the emitting region, estimate the super massive black hole mass, find the dominant emission mechanism in the close vicinity of the super massive black hole, search for quasi-periodic oscillations in time series data and several other physical parameters of blazars. Flux and spectral variability is also a dominant tool to explain jet as well as disk emission from blazars at different epochs of observations.

Fuzzy Nonlinear Regression Analysis Using Fuzzified Neural Networks for Fault Diagnosis of Chemical Plants

2011 ◽  
Vol 15 (3) ◽  
pp. 336-344 ◽  
Author(s):  
Daisaku Kimura ◽  
◽  
Manabu Nii ◽  
Takafumi Yamaguchi ◽  
Yutaka Takahashi ◽  
...  
Keyword(s):  
Neural Network ◽  
Nonlinear Regression ◽  
Time Series Data ◽  
Numerical Data ◽  
The State ◽  
Series Data ◽  
Target System ◽  
Chemical Plants ◽  
Domain Experts ◽  
Recorded Data

In systems such as chemical plants or circulatory systems, failure of piping, sensors or valves causes serious problems. These failures can be avoided by the increase in sensors and operators for condition monitoring. However, since adding sensors and operators leads to an increase in cost, it is difficult to realize. In this paper, a technique of diagnosing target systems based on a fuzzy nonlinear regression is proposed by using a fuzzified neural network that is trained with time-series data with reliability grades. Our proposed technique uses numerical data recorded by the existing monitoring system. Reliability grades are beforehand given to the recorded data by domain experts. The state of a target system is determined based on the fuzzy output from the trained fuzzified neural network. Our proposed technique makes us determine easily the state of the target systems. Our proposed technique is flexibly applicable to various types of systems by considering some parameters for failure determination of target systems.

Sewer system flow components identification using signal processing

2010 ◽  
Vol 62 (1) ◽  
pp. 106-114
Author(s):  
F. A. Dorval ◽  
B. Chocat ◽  
E. Emmanuel ◽  
G. Lipeme Kouyi
Keyword(s):  
Signal Processing ◽  
Time Series Data ◽  
Continuous Model ◽  
Series Data ◽  
Time Step ◽  
Sewer System ◽  
Long Time ◽  
Recorded Data ◽  
Flow Components ◽  
Main Components

The development of a continuous model to simulate the behaviour of sewer systems requires detailed information on each component of the flows contributing to the global discharge. In this paper authors investigate a novel method based on signal processing and long time series data implemented with a 2 min time step (flow rate, conductivity, pH and turbidity) in order to identify the dry weather components in a separated stormwater sewer system draining an industrial catchment. The wavelet analysis is applied to the recorded data to identify main components in dry weather flow after the removing of the signal noise. This paper highlights also a method to detect inflow into sewer system and shows how hydrological modelling can be used to characterise the relevant components. These techniques could be used as a basis for several applications.

scholarly journals An Innovative Concept for a Multivariate Plausibility Assessment of Simultaneously Recorded Data

Animals ◽  
2020 ◽  
Vol 10 (8) ◽  
pp. 1412
Author(s):  
André Mensching ◽  
Marleen Zschiesche ◽  
Jürgen Hummel ◽  
Armin Otto Schmitt ◽  
Clément Grelet ◽  
...  
Keyword(s):  
Time Series Data ◽  
Extreme Values ◽  
Blood Parameters ◽  
Management Tool ◽  
Series Data ◽  
Complex Data ◽  
Climate Data ◽  
Data Set ◽  
Continuous Measurements ◽  
Recorded Data

The aim of this work was to develop an innovative multivariate plausibility assessment (MPA) algorithm in order to differentiate between ‘physiologically normal’, ‘physiologically extreme’ and ‘implausible’ observations in simultaneously recorded data. The underlying concept is based on the fact that different measurable parameters are often physiologically linked. If physiologically extreme observations occur due to disease, incident or hormonal cycles, usually more than one measurable trait is affected. In contrast, extreme values of a single trait are most likely implausible if all other traits show values in a normal range. For demonstration purposes, the MPA was applied on a time series data set which was collected on 100 cows in 10 commercial dairy farms. Continuous measurements comprised climate data, intra-reticular pH and temperature, jaw movement and locomotion behavior. Non-continuous measurements included milk yield, milk components, milk mid-infrared spectra and blood parameters. After the application of the MPA, in particular the pH data showed the most implausible observations with approximately 5% of the measured values. The other traits showed implausible values up to 2.5%. The MPA showed the ability to improve the data quality for downstream analyses by detecting implausible observations and to discover physiologically extreme conditions even within complex data structures. At this stage, the MPA is not a fully developed and validated management tool, but rather corresponds to a basic concept for future works, which can be extended and modified as required.

Experimental and Numerical Investigations on a Rotating Centrifugal Compressor

2012 ◽  
Author(s):  
Patricio Almeida ◽  
Claude Gibert ◽  
Xavier Leblanc ◽  
Jean-Philippe Ousty ◽  
Fabrice Thouverez
Keyword(s):  
Dynamic Behavior ◽  
Centrifugal Compressor ◽  
Signal Transmission ◽  
Laser Doppler Vibrometer ◽  
Rear Side ◽  
Scanning Laser Doppler Vibrometer ◽  
Advantages And Disadvantages ◽  
Slip Ring ◽  
Compressor Impeller ◽  
Common Technique

Controlling the dynamic behavior of turbomachines requires an experimental validation phase to ensure their safety. The application of two experimental techniques to measure the modal properties of a rotating centrifugal compressor impeller is described in this paper. The impeller was tested in a vacuum chamber with excitation provided by piezoelectric actuators mounted on the rear side of the impeller disk. The most common technique used to measure the dynamic behavior of a rotating structure is based on strain gauges and a telemetry system or a slip ring for signal transmission. Nevertheless, in some cases this method is an intrusive technique that could introduce damping and blade mistiming, and it can also be time consuming to prepare. Strain gauge measurement has been compared to measurements performed under the same conditions by Scanning Laser Doppler Vibrometer associated with a derotator optical system, which allows measurement at fixed points on a rotating part. This work focuses on the study of the dynamic behavior of a centrifugal compressor impeller in view to preparing stator contact interaction tests requiring precise characterization of frequencies and nodal diameters and of the influence of rotation speed and other possible parameters. The advantages and disadvantages of the two methods used have been assessed for this particular application. A correlation between the experiments and the numerical simulations using the finite element method is provided.

scholarly journals Coupled Delft3D-Object Model to Predict Mobility of Munition on Sandy Seafloor

Fluids ◽  
2021 ◽  
Vol 6 (9) ◽  
pp. 330
Author(s):  
Peter C. Chu ◽  
Vinicius S. Pessanha ◽  
Chenwu Fan ◽  
Joseph Calantoni
Keyword(s):  
Experimental Data ◽  
Sediment Transport ◽  
Time Series Data ◽  
Major Axis ◽  
Series Data ◽  
Physical Parameters ◽  
Object Model ◽  
Wave Direction ◽  
Rolling Moment ◽  
Object Mobility

The coupled Delft3D-object model has been developed to predict the mobility and burial of objects on sandy seafloors. The Delft3D model is used to predict seabed environmental factors such as currents, waves (peak wave period, significant wave height, wave direction), water level, sediment transport, and seabed change, which are taken as the forcing term to the object model consisting of three components: (a) physical parameters such as diameter, length, mass, and rolling moment; (b) dynamics of the rolling cylinder around its major axis; (c) an empirical sediment scour model with re-exposure parameterization. The model is compared with the observational data collected from a field experiment from 21 April to 13 May 2013 off the coast of Panama City, Florida. The experimental data contain both object mobility using sector scanning sonars and maintenance divers as well as simultaneous environmental time series data of the boundary layer hydrodynamics and sediment transport conditions. Comparison between modeled and observed data clearly shows the model’s capabilities and limitations.

scholarly journals Fishery Landing Forecasting Using Wavelet-Based Autoregressive Integrated Moving Average Models

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Ani Shabri ◽  
Ruhaidah Samsudin
Keyword(s):  
Time Series Data ◽  
Moving Average ◽  
Arima Model ◽  
Peninsular Malaysia ◽  
Series Data ◽  
Proposed Model ◽  
Moving Average Models ◽  
Recorded Data ◽  
The Individual

The accuracy of the wavelet-ARIMA (WA) model in monthly fishery landing forecasting is investigated in the study. In the first part of the study, the discrete wallet transform (DWT) is used to decompose fishery landing time series data. Then ARIMA, as a powerful forecasting tool, is implemented to predict each wavelet transform subseries components independently. Finally, the prediction results of the modeled subseries components are summed to formulate an ensemble forecast for the original fishery landing series. To assess the effectiveness of this model, monthly fishery landing recorded data from East Johor and Pahang states of Peninsular Malaysia have been used as a case study. The result of the study shows that the proposed model was found to provide more accurate fishery landing series forecasts than the individual ARIMA model.

Extremely peculiar spectrum of the primary component of the eclipsing binary HD 66051

2019 ◽  
Vol 15 (S350) ◽  
pp. 412-414
Author(s):  
E. Niemczura ◽  
P. A. Kołaczek-Szymański ◽  
F. Castelli ◽  
S. Hubrig ◽  
S. P. Järvinen ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Primary Component ◽  
Series Data ◽  
Physical Parameters ◽  
Orbital Parameters ◽  
Chemically Peculiar ◽  
Peculiar Stars ◽  
Chemically Peculiar Stars ◽  
Chemical Peculiarity

AbstractHD 66051 is an eclipsing and spectroscopic double-lined binary (SB2), hosting two chemically peculiar stars: a highly peculiar B star as primary and an Am star as secondary. The investigation of the new high-resolution UVES spectrum of HD 66051 allowed us to decide on the chemical peculiarity type of both components with more reliability. An analysis of TESS photometric time series data will further specify the physical parameters of the stars and the orbital parameters of the system.

scholarly journals Coupled Delft3D-Object Model to Predict Mobility and Burial of Munition on Sandy Floor

2021 ◽  
Author(s):  
Peter C. Chu ◽  
Vinicius S. Pessanha ◽  
Chenwu Fan
Keyword(s):  
Sediment Transport ◽  
Time Series Data ◽  
Development Program ◽  
Environmental Research ◽  
Series Data ◽  
Physical Parameters ◽  
Object Model ◽  
Wave Direction ◽  
Peak Period ◽  
Rolling Moment

Coupled Delft3D-object model has been developed to predict object’s mobility and burial on sandy seafloor. The Delft3D model is used to predict seabed environment such as currents, waves (peak period, significant wave height, wave direction), water level, sediment transport, and seabed change, which are taken as the forcing term to the object model consisting of three components: (a) object‘s physical parameters such as diameter, length, mass, and rolling moment, (b) dynamics of rolling cylinder around its major axis, and (c) empirical sediment scour model with re-exposure parameterization. The model is compared with the observational data collected from a field experiment from 21 April to 23 May 2013 off the coast of Panama City, Florida funded by the Department of Defense Strategic Environmental Research and Development Program. The experimental data contain both objects’ mobility using sector scanning and pencil beam sonars and simultaneous environmental time series data of the boundary layer hydrodynamics and sediment transport conditions. Comparison between modeled and observed data clearly show the model capability.

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