scholarly journals Monitoring and diagnostics of special-purpose turbomachines

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Małgorzata Gizelska
Keyword(s):  
Real Time ◽  
Measurement Data ◽  
Magnetic Bearing ◽  
Operating Conditions ◽  
Active Magnetic Bearing ◽  
Diagnostic Tools ◽  
Compression Process ◽  
Rotating System ◽  
On Line ◽  
Monitoring And Diagnostics

Abstract In the operation of special-purpose turbomachines, diagnostic tools are necessary. They enable control of the machine technical state and its operation parameters in the on-line mode. The acquisition and processing of the measurement data in real time is crucial as they are indicators of the machine functioning under various operating conditions. The paper presents two types of computer designed diagnostic tools to monitor in real time the dynamic and thermodynamic parameters of special-purpose turbomachines. The first one monitors the dynamics of the rotating system with an active magnetic bearing, the second - monitors the instant value of polytropic efficiency of the compression process, which was designed for the industrial machine.

Monitoring and Diagnostics of the Rotating System with an Active Magnetic Bearing

2013 ◽  
Vol 198 ◽  
pp. 547-552
Author(s):  
Małgorzata Gizelska ◽  
Dorota Kozanecka ◽  
Zbigniew Kozanecki
Keyword(s):  
Diagnostic System ◽  
Magnetic Bearing ◽  
Active Magnetic Bearing ◽  
Active Magnetic Bearings ◽  
Rotating System ◽  
Automatic Mode ◽  
Actual Operation ◽  
Advanced Information Technology ◽  
Monitoring And Diagnostics ◽  
Proper Operation

In the paper, a concept and selected procedures of the specialized software using advanced information technology for the diagnostic system dedicated for systems of rotating machines with active magnetic bearings will be presented. It is used in the actual operation of the machine, enabling an increase of its reliability. The paper presents some selected results of control of the proper operation of the mechatronic rotating system, carried out in the automatic mode.

scholarly journals Detection of drinking water contamination event with Mahalanobis distance method, using on-line monitoring sensors and manual measurement data

2018 ◽  
Vol 18 (6) ◽  
pp. 2133-2141 ◽  
Author(s):  
S. Dejus ◽  
A. Nescerecka ◽  
G. Kurcalts ◽  
T. Juhna
Keyword(s):  
Drinking Water ◽  
Real Time ◽  
Mahalanobis Distance ◽  
Measurement Data ◽  
Early Warning Systems ◽  
Operating Conditions ◽  
Distance Method ◽  
Biological Contamination ◽  
On Line ◽  
Contamination Events

Abstract Concerns about drinking water (DW) quality contamination during water distribution raise a need for real-time monitoring and rapid contamination detection. Early warning systems (EWS) are a potential solution. The EWS consist of multiple conventional sensors that provide the real-time measurements and algorithms that allow the recognizing of contamination events from normal operating conditions. In most cases, these algorithms have been established with artificial data, while data from real and biological contamination events are limited. The goal of the study was the event detection performance of the Mahalanobis distance method in combination with on-line DW quality monitoring sensors and manual measurements of grab samples for potential DW biological contamination scenarios. In this study three contamination scenarios were simulated in a pilot-scale DW distribution system: untreated river water, groundwater and wastewater intrusion, which represent realistic contamination scenarios and imply biological contamination. Temperature, electrical conductivity (EC), total organic carbon (TOC), chlorine ion (Cl-), oxidation–reduction potential (ORP), pH sensors and turbidity measurements were used as on-line sensors and for manual measurements. Novel adenosine-triphosphate and flow cytometric measurements were used for biological water quality evaluation. The results showed contamination detection probability from 56% to 89%, where the best performance was obtained with manual measurements. The probability of false alarm was 5–6% both for on-line and manual measurements. The Mahalanobis distance method with DW quality sensors has a good potential to be applied in EWS. However, the sustainability of the on-line measurement system and/or the detection algorithm should be improved.

Some Nonlinear Effects of Magnetic Bearings

1999 ◽  
Author(s):  
Norbert Steinschaden ◽  
Helmut Springer
Keyword(s):  
Equations Of Motion ◽  
Period Doubling ◽  
Path Following ◽  
Nonlinear Effects ◽  
Magnetic Bearing ◽  
Operating Conditions ◽  
Active Magnetic Bearing ◽  
Nonlinear Phenomena ◽  
Amb System ◽  
Large Rotor

Abstract In order to get a better understanding of the dynamics of active magnetic bearing (AMB) systems under extreme operating conditions a simple, nonlinear model for a radial AMB system is investigated. Instead of the common way of linearizing the magnetic forces at the center position of the rotor with respect to rotor displacement and coil current, the fully nonlinear force to displacement and the force to current characteristics are used. The AMB system is excited by unbalance forces of the rotor. Especially for the case of large rotor eccentricities, causing large rotor displacements, the behaviour of the system is discussed. A path-following analysis of the equations of motion shows that for some combinations of parameters well-known nonlinear phenomena may occur, as, for example, symmetry breaking, period doubling and even regions of global instability can be observed.

Artificial Intelligence and Data Analytics for Virtual Flow Metering

2021 ◽  
Author(s):  
Anton Gryzlov ◽  
Liliya Mironova ◽  
Sergey Safonov ◽  
Muhammad Arsalan
Keyword(s):  
Machine Learning ◽  
Multiphase Flow ◽  
Real Time ◽  
Production Control ◽  
Measurement Data ◽  
Sufficient Accuracy ◽  
Operating Conditions ◽  
Machine Learning Techniques ◽  
Flow Metering ◽  
Oil Gas

Abstract Modern challenges in reservoir management have recently faced new opportunities in production control and optimization strategies. These strategies in turn rely on the availability of monitoring equipment, which is used to obtain production rates in real-time with sufficient accuracy. In particular, a multiphase flow meter is a device for measuring the individual rates of oil, gas and water from a well in real-time without separating fluid phases. Currently, there are several technologies available on the market but multiphase flow meters generally incapable to handle all ranges of operating conditions with satisfactory accuracy in addition to being expensive to maintain. Virtual Flow Metering (VFM) is a mathematical technique for the indirect estimation of oil, gas and water flowrates produced from a well. This method uses more readily available data from conventional sensors, such as downhole pressure and temperature gauges, and calculates the multiphase rates by combining physical multiphase models, various measurement data and an optimization algorithm. In this work, a brief overview of the virtual metering methods is presented, which is followed by the application of several advanced machine-learning techniques for a specific case of multiphase production monitoring in a highly dynamic wellbore. The predictive capabilities of different types of machine learning instruments are explored using a model simulated production data. Also, the effect of measurement noise on the quality of estimates is considered. The presented results demonstrate that the data-driven methods are very capable to predict multiphase flow rates with sufficient accuracy and can be considered as a back-up solution for a conventional multiphase meter.

scholarly journals Nonlinear Control of an Active Magnetic Bearing System Achieved Using a Fuzzy Control with Radial Basis Function Neural Network

2014 ◽  
Vol 2014 ◽  
pp. 1-18 ◽  
Author(s):  
Seng-Chi Chen ◽  
Van-Sum Nguyen ◽  
Dinh-Kha Le ◽  
Nguyen Thi Hoai Nam
Keyword(s):  
Neural Network ◽  
Radial Basis Function ◽  
Basis Function ◽  
Fuzzy Logic Controller ◽  
Magnetic Bearing ◽  
Operating Conditions ◽  
Active Magnetic Bearing ◽  
Highly Nonlinear ◽  
Radial Basis ◽  
Amb System

Studies on active magnetic bearing (AMB) systems are increasing in popularity and practical applications. Magnetic bearings cause less noise, friction, and vibration than the conventional mechanical bearings; however, the control of AMB systems requires further investigation. The magnetic force has a highly nonlinear relation to the control current and the air gap. This paper proposes an intelligent control method for positioning an AMB system that uses a neural fuzzy controller (NFC). The mathematical model of an AMB system comprises identification followed by collection of information from this system. A fuzzy logic controller (FLC), the parameters of which are adjusted using a radial basis function neural network (RBFNN), is applied to the unbalanced vibration in an AMB system. The AMB system exhibited a satisfactory control performance, with low overshoot, and produced improved transient and steady-state responses under various operating conditions. The NFC has been verified on a prototype AMB system. The proposed controller can be feasibly applied to AMB systems exposed to various external disturbances; demonstrating the effectiveness of the NFC with self-learning and self-improving capacities is proven.

scholarly journals Accurate Real Time On-Line Estimation of State-of-Health and Remaining Useful Life of Li ion Batteries

2020 ◽  
Vol 10 (21) ◽  
pp. 7836
Author(s):  
Cher Ming Tan ◽  
Preetpal Singh ◽  
Che Chen
Keyword(s):  
Lithium Ion Batteries ◽  
Real Time ◽  
Estimation Method ◽  
Lithium Ion ◽  
Threshold Level ◽  
Remaining Useful Life ◽  
Operating Conditions ◽  
State Of Health ◽  
On Line ◽  
Useful Life

Inaccurate state-of-health (SoH) estimation of battery can lead to over-discharge as the actual depth of discharge will be deeper, or a more-than-necessary number of charges as the calculated SoC will be underestimated, depending on whether the inaccuracy in the maximum stored charge is over or under estimated. Both can lead to increased degradation of a battery. Inaccurate SoH can also lead to the continuous use of battery below 80% actual SoH that could lead to catastrophic failures. Therefore, an accurate and rapid on-line SoH estimation method for lithium ion batteries, under different operating conditions such as varying ambient temperatures and discharge rates, is important. This work develops a method for this purpose, and the method combines the electrochemistry-based electrical model and semi-empirical capacity fading model on a discharge curve of a lithium-ion battery for the estimation of its maximum stored charge capacity, and thus its state of health. The method developed produces a close form that relates SoH with the number of charge-discharge cycles as well as operating temperatures and currents, and its inverse application allows us to estimate the remaining useful life of lithium ion batteries (LiB) for a given SoH threshold level. The estimation time is less than 5 s as the combined model is a closed-form model, and hence it is suitable for real time and on-line applications.

scholarly journals Exploration of NDE Properties of AMB Supported Rotors for Structural Damage Detection

2010 ◽  
Author(s):  
Jerzy T. Sawicki ◽  
Dmitry L. Storozhev ◽  
John D. Lekki
Keyword(s):  
Structural Damage ◽  
Magnetic Bearing ◽  
Active Magnetic Bearing ◽  
Line Detection ◽  
Control Loop ◽  
Structural Damage Detection ◽  
Cracked Rotor ◽  
Rotating Shaft ◽  
On Line ◽  
Combination Frequencies

This paper addresses self-diagnostic properties of AMB (active magnetic bearing) supported rotors for on-line detection of the transverse crack on a rotating shaft. In addition to pure levitation, the rotor supporting bearing also serves as an actuator that transforms current signals additionally injected into the control loop into the superimposed specially selected excitation forces into the suspended rotor. These additional excitations induce combination frequencies in the rotor response, providing unique signatures for the presence of crack. The background of theoretical modeling, experimental and computer simulation results for the AMB supported cracked rotor with self-diagnostic excitation forces are presented and discussed.

The Development and Design of a Laser Detection System for Tire Thickness Measurement

2013 ◽  
Vol 418 ◽  
pp. 128-131
Author(s):  
King Sun Lee
Keyword(s):  
Standard Deviation ◽  
Real Time ◽  
Detection System ◽  
Measurement Data ◽  
Thickness Measurement ◽  
Inspection System ◽  
Laser Sensors ◽  
Repeatability Error ◽  
On Line ◽  
Measuring Machine

This system is a self-developed real-time thickness inspection system including high-precision laser sensors and a mobile platform for on-line detection of tire rubber skin. The measurement data is used to calculate the standard deviation and process capability indices, and to evaluate measurement capacity. The system is a real-time measurement system in which the obtained measuring data compare with the standard value and show any errors. A technician can adjust the process parameters precisely on-line to improve product quality. The standard deviation of repeatability of the system for height is within +/- 0.0081 mm. The repeatability error of the horizontal sliding rail is within 0.0145mm, while the measurement error between this system and a coordinated measuring machine is within 0.028mm.

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