scholarly journals Novel Cyclo-Non-Stationary Indicators for Monitoring of Rotating Machinery Operating Under Speed and Load Varying Conditions

2021 ◽  
Author(s):  
Alexandre Mauricio ◽  
Dustin M Helm ◽  
Markus Timusk ◽  
Jerome Antoni ◽  
Konstantinos Gryllias
Keyword(s):  
Industrial Process ◽  
Rotating Machinery ◽  
Operating Conditions ◽  
Cyclic Behavior ◽  
Spectral Correlation ◽  
Rotating Speed ◽  
Modulation Spectrum ◽  
Novel Approach ◽  
Cyclostationary Signals ◽  
Bearing Damage

Abstract Condition monitoring arises as a valuable industrial process in order to assess the health of rotating machinery, providing early and accurate warning of potential failures and allowing for the planning and effective realization of preventative maintenance actions. In complex machines the failure indications of an early bearing damage are weak compared to other sources of excitations. Vibration analysis is most widely used and various methods have been proposed. In a number of applications, changes in the operating conditions (speed/load) influence the vibration sources and change the frequency and amplitude characteristics of the vibroacoustic signature, making them nonstationary. Recently an emerging interest has been focused on modelling rotating machinery signals as cyclostationary. Classical cyclostationary tools, such as Cyclic Spectral Correlation Density (CSCD) and Cyclic Modulation Spectrum (CMS), can be used to extract information about the cyclic behavior of cyclostationary signals, under the assumption of nearly constant rotating speed. Global diagnostic indicators have been proposed as a measure of cyclostationarity under steady operating conditions. In order to overcome this limitation a generalization of both SCD and CMS functions have been proposed displaying cyclic Order versus Frequency as well as diagnostic indicators of cyclo-non-stationarity in order to cover the speed varying operating conditions. The scope of this paper is to propose a novel approach for the analysis of cyclononstationary signals to cover the simultaneous and independently varying speed and load operating conditions. The effectiveness of the approach is evaluated on simulated and real signals captured on a dedicated test rig.

scholarly journals Novel Cyclo-Non-Stationary Indicators for Monitoring of Rotating Machinery Operating Under Speed and Load Varying Conditions

2020 ◽  
Author(s):  
Alexandre Mauricio ◽  
Dustin Helm ◽  
Markus Timusk ◽  
Jerome Antoni ◽  
Konstantinos Gryllias
Keyword(s):  
Condition Monitoring ◽  
Gas Turbines ◽  
Business Models ◽  
Industrial Process ◽  
Rotating Machinery ◽  
Operating Conditions ◽  
Cyclic Behavior ◽  
Spectral Correlation ◽  
Time Frequency ◽  
Novel Approach

Abstract Condition monitoring arises as a valuable industrial process in order to assess the health of rotating machinery, providing early and accurate warning of potential failures and allowing for the planning and effective realization of preventative maintenance actions. Nowadays machinery (gas turbines, wind turbines etc.) manufacturers adopt new business models, providing not only the equipment itself but additionally taking on responsibilities of condition monitoring, by embedding sensors and health monitoring systems within each unit and prompting maintenance actions when necessary. Among others, rolling element bearings are one of the most critical components in rotating machinery. In complex machines the failure indications of an early bearing damage are weak compared to other sources of excitations (e.g. gears, shafts, rotors etc.). Vibration analysis is most widely used and various methods have been proposed, including analysis in the time and frequency domain. In a number of applications, changes in the operating conditions (speed/load) influence the vibration sources and change the frequency and amplitude characteristics of the vibroacoustic signature, making them nonstationary. Under changing environments, where speed and load vary, the assumption of quasi-stationary is not appropriate and as a result a number of time-frequency and time-order representations have been introduced, such as the Short Time Fourier Transform and the Wavelets. Recently an emerging interest has been focused on modelling rotating machinery signals as cyclostationary, which is a particular class of non-stationary stochastic processes. The classical cyclostationary tools, such as the Cyclic Spectral Correlation Density (CSCD) and the Cyclic Modulation Spectrum (CMS), can be used in order to extract interesting information about the cyclic behavior of cyclostationary signals, only under the assumption that the speed of machinery is constant or nearly constant. Global diagnostic indicators have been proposed as a measure of cyclostationarity under steady operating conditions. In order to overcome this limitation a generalization of both SCD and CMS functions have been proposed displaying cyclic Order versus Frequency as well as diagnostic indicators of cyclo-non-stationarity in order to cover the speed varying operating conditions. The scope of this paper is to propose a novel approach for the analysis of cyclo-non-stationary signals based on the generalization of indicators of cyclo-non-stationarity in order to cover the simultaneous and independently varying speed and load operating conditions. The effectiveness of the approach is evaluated on simulated and real signals captured on a dedicated test rig.

scholarly journals Application of Cyclo-Non-Stationary Indicators for Bearing Monitoring Under Varying Operating Conditions

2017 ◽  
Author(s):  
Konstantinos Gryllias ◽  
Simona Moschini ◽  
Jerome Antoni
Keyword(s):  
Frequency Domain ◽  
Condition Monitoring ◽  
Health Monitoring ◽  
Computational Cost ◽  
Rotating Machinery ◽  
Operating Conditions ◽  
Vibration Monitoring ◽  
Cyclic Behavior ◽  
Diagnostic Features ◽  
Time Frequency

Condition monitoring assesses the operational health of rotating machinery, in order to provide early and accurate warning of potential failures such that preventative maintenance actions may be taken. To achieve this target, manufacturers start taking on the responsibilities of engine condition monitoring, by embedding health monitoring systems within each engine unit and prompting maintenance actions when necessary. Several types of condition monitoring are used including oil debris monitoring, temperature monitoring and vibration monitoring. Among them, vibration monitoring is the most widely used technique. Machine vibro-acoustic signatures contain pivotal information about its state of health. The current work focuses on one part of the diagnosis stage of condition monitoring for engine bearing health monitoring as bearings are critical components in rotating machinery. A plethora of signal processing tools and methods applied at the time domain, the frequency domain, the time-frequency domain and the time-scale domain have been presented in order to extract valuable information by proposing different diagnostic features. Among others, an emerging interest has been reported on modeling rotating machinery signals as cyclostationary, which is a particular class of non-stationary stochastic processes. A process x(t) is said to be nth-order cyclostationary with period T if its nth-order moments exist and are periodic with period T. Several tools, such as the Spectral Correlation Density (SCD) and the Cyclic Modulation Spectrum (CMS) can be used in order to extract interesting information concerning the cyclic behavior of cyclostationary signals. In order to measure the cyclostationarity from order 1 to 4, concise and global indicators have been proposed. However, in a number of applications such as aircraft engines and wind turbines the characteristic vibroacoustic signatures of rotating machinery depend on the operating conditions of the rotational speed and/or the load. During the last decades fault diagnostics of rotating machinery under variable speed/load has attracted a lot of interest. The classical cyclostationary tools can be used under the assumption that the speed of machinery is constant or nearly constant, otherwise the vibroacoustic signal becomes cyclo-non-stationary. In order to overcome this limitation a generalization of both SCD and CMS functions have been proposed displaying cyclic Order versus Frequency. The goal of this paper is to propose a novel approach for the analysis of cyclo-nonstationary signals based on the generalization of indicators of cyclostationarity in order to cover the speed varying conditions. The proposed indicators of cyclo-non-stationarity (ICNS) are expected to summarize the information at various statistical orders and at lower computational cost compared to the Order-Frequency SCD or CMS. This generalization is realized by introducing a new speed-dependent angle averaging operator. The effectiveness of the approach is evaluated on an acceleration signal captured on the casing of an aircraft engine gearbox, provided by SAFRAN, in the frames of SAFRAN contest which took place at the Surveillance 8 International Conference.

A Multiple Harmonic Open-Loop Controller for Hydro/Aerodynamic Force Measurements in Rotating Machinery Using Magnetic Bearings

2002 ◽  
Vol 124 (4) ◽  
pp. 827-834 ◽  
Author(s):  
D. O. Baun ◽  
E. H. Maslen ◽  
C. R. Knospe ◽  
R. D. Flack
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
Open Loop ◽  
Rotating Machinery ◽  
Operating Conditions ◽  
Rotor Vibration ◽  
Aerodynamic Forces ◽  
Analog Input ◽  
Input And Output ◽  
The Time Domain

Inherent in the construction of many experimental apparatus designed to measure the hydro/aerodynamic forces of rotating machinery are features that contribute undesirable parasitic forces to the measured or test forces. Typically, these parasitic forces are due to seals, drive couplings, and hydraulic and/or inertial unbalance. To obtain accurate and sensitive measurement of the hydro/aerodynamic forces in these situations, it is necessary to subtract the parasitic forces from the test forces. In general, both the test forces and the parasitic forces will be dependent on the system operating conditions including the specific motion of the rotor. Therefore, to properly remove the parasitic forces the vibration orbits and operating conditions must be the same in tests for determining the hydro/aerodynamic forces and tests for determining the parasitic forces. This, in turn, necessitates a means by which the test rotor’s motion can be accurately controlled to an arbitrarily defined trajectory. Here in, an interrupt-driven multiple harmonic open-loop controller was developed and implemented on a laboratory centrifugal pump rotor supported in magnetic bearings (active load cells) for this purpose. This allowed the simultaneous control of subharmonic, synchronous, and superharmonic rotor vibration frequencies with each frequency independently forced to some user defined orbital path. The open-loop controller was implemented on a standard PC using commercially available analog input and output cards. All analog input and output functions, transformation of the position signals from the time domain to the frequency domain, and transformation of the open-loop control signals from the frequency domain to the time domain were performed in an interrupt service routine. Rotor vibration was attenuated to the noise floor, vibration amplitude ≈0.2 μm, or forced to a user specified orbital trajectory. Between the whirl frequencies of 14 and 2 times running speed, the orbit semi-major and semi-minor axis magnitudes were controlled to within 0.5% of the requested axis magnitudes. The ellipse angles and amplitude phase angles of the imposed orbits were within 0.3 deg and 1.0 deg, respectively, of their requested counterparts.

Experimental study of mild steel cutting process by using the plasma arc method

2021 ◽  
Vol 108 (2) ◽  
pp. 75-85
Author(s):  
H.M. Magid
Keyword(s):  
Industrial Process ◽  
Scanning Speed ◽  
Cutting Parameters ◽  
Operating Conditions ◽  
Kerf Width ◽  
Cutting Process ◽  
Plasma Cutting ◽  
Plasma Arc ◽  
Cutting Equipment

Purpose: In this study, plasma arc cutting (PAC) is an industrial process widely used for cutting various away types of metals in several operating conditions. Design/methodology/approach: It is carried out a systematic or an authoritative inquiry to discover and examine the fact, the plasma cutting process is to establish the accuracy and the quality of the cut in this current paper assessed a good away to better the cutting process. Findings: It found that the effect of parameters on the cutting quality than on the results performed to accomplish by statistical analysis. Research limitations/implications: The objective of the present work paper is to achieve cutting parameters, thus the quality of the cutting process depends upon the plasma gas pressure, scanning speed, cutting power, and cutting height. Practical implications: The product of the plasma cutting process experimentally has been the quality of the cutting equipment that was installed to monitor kerf width quality by exam the edge roughness, kerf width, and the size of the heat-affected zone (HAZ). Originality/value: The results reveal that were technically possessed of including all the relevant characteristics, then a quality control for the cutting and describe the consequence of the process parameters.

scholarly journals Deep learning-based anomaly-onset aware remaining useful life estimation of bearings

2021 ◽  
Vol 7 ◽  
pp. e795
Author(s):  
Pooja Vinayak Kamat ◽  
Rekha Sugandhi ◽  
Satish Kumar
Keyword(s):  
Deep Learning ◽  
Anomaly Detection ◽  
Short Term Memory ◽  
Rotating Machinery ◽  
Remaining Useful Life ◽  
Operating Conditions ◽  
Learning Models ◽  
Vibration Data ◽  
Degradation Data ◽  
Useful Life

Remaining Useful Life (RUL) estimation of rotating machinery based on their degradation data is vital for machine supervisors. Deep learning models are effective and popular methods for forecasting when rotating machinery such as bearings may malfunction and ultimately break down. During healthy functioning of the machinery, however, RUL is ill-defined. To address this issue, this study recommends using anomaly monitoring during both RUL estimator training and operation. Essential time-domain data is extracted from the raw bearing vibration data, and deep learning models are used to detect the onset of the anomaly. This further acts as a trigger for data-driven RUL estimation. The study employs an unsupervised clustering approach for anomaly trend analysis and a semi-supervised method for anomaly detection and RUL estimation. The novel combined deep learning-based anomaly-onset aware RUL estimation framework showed enhanced results on the benchmarked PRONOSTIA bearings dataset under non-varying operating conditions. The framework consisting of Autoencoder and Long Short Term Memory variants achieved an accuracy of over 90% in anomaly detection and RUL prediction. In the future, the framework can be deployed under varying operational situations using the transfer learning approach.

scholarly journals Orange-based and Lemon-based Adsorbents with Controlled Grain for an Efficient Elimination of Cationic and Anionic Dyes from Textile Dyeing Wastewater

2021 ◽  
Author(s):  
G. Pascual ◽  
M. Riba-Moliner ◽  
J. M. Canal ◽  
J. Garcia-Raurich
Keyword(s):  
Aqueous Solutions ◽  
Industrial Process ◽  
Operating Conditions ◽  
Dyeing Wastewater ◽  
Anionic Dyes ◽  
Chemically Modified ◽  
Natural Adsorbents ◽  
Textile Dyeing ◽  
Efficient Elimination ◽  
Textile Dyeing Wastewater

Abstract Physically and chemically modified orange and lemon mesocarps are used as natural adsorbents for both cationic and anionic dyes from wastewaters of textile dyeing industry. Adsorptivity of the orange-based and lemon-based adsorbents to the dyes are studied simulating a batch and a continuous industrial process. Thus, the most suitable operating conditions to achieve the maximum adsorption yield are provided. Results demonstrate that treated orange and lemon mesocarps can be used as excellent reusable adsorbents to the removal of cationic and anionic dyes from aqueous solutions. Moreover, the recovery of the adsorbed dye is also reliable and proved.

Developing of Polypyrrole Coating on Rotating Steel Cylinder for Improving its Corrosion Resistance

2013 ◽  
Vol 685 ◽  
pp. 277-282
Author(s):  
Ahmed H. El-Shazly ◽  
H.A. Al-Turaif
Keyword(s):  
Corrosion Resistance ◽  
Rotational Speed ◽  
Saline Solution ◽  
Monomer Concentration ◽  
Operating Conditions ◽  
Solution Ph ◽  
Steel Cylinder ◽  
Sodium Tartrate ◽  
Rotating Speed ◽  
Pyrrole Monomer

This work investigates the possibility of using polypyrrole (PPy) coating for improving the corrosion resistance of rotating cylinder subjected to saline solution. Galvanostatic technique was used for layer formation under different conditions of current density, pyrrole monomer concentration, sodium tartrate concentration and solution pH. The potentiodynamic technique was used for examination of PPy coated steel in corrosive medium composed of 3.5%NaCl under different rotating speed ranging from 200 to 1000 rpm. The formed PPy layer was investigated for its corrosion resistance using 3.5% NaCl solution under different rotational speed using the potentiodynamic technique. The preliminary results showed that coating steel with polypyrrole layer under different rotational speed can improve its corrosion resistance by a factor ranging from 1.2 to 1.88 depending on the operating conditions

Spectral Imaging: Fluorescence and Brightfield

2001 ◽  
Vol 7 (S2) ◽  
pp. 20-21
Author(s):  
Richard Levenson
Keyword(s):  
Imaging Spectroscopy ◽  
Industrial Process ◽  
Spectral Imaging ◽  
Vascular Integrity ◽  
Maximum Information ◽  
Expression Arrays ◽  
Novel Approach ◽  
Multiple Wavelengths ◽  
Industrial Process Control ◽  
Multicolor Fluorescence

Spectral imaging is a relatively new technique that provides images of a scene at multiple wavelengths and can generate precise optical spectra at every pixel. Mathematical approaches may then be used to extract the maximum information from the spectral image. Spectral imaging is routinely used in “remote sensing”, that is, the analysis of distant landscapes and structures from airplanes or satellites. Minor differences in spectra can be used to detect different crops, or mineral deposits, for example. Closer in, spectral imaging has uses in industrial process control, detection of otherwise invisible bruising in fruit, vascular integrity in transplanted organs, and so on. Finally, spectral imaging has newly been adapted for easy use in microscopy, with applications in surgical pathology, multicolor fluorescence and immunohistochemistry, and in DNA expression arrays, among others. A variety of technologies can be used to perform imaging spectroscopy, including Fourier transform interferometry, tunable filters, line-scanning prism or gratings-based devices, and others based on polarization effects. Recently, CRI has developed a novel approach for brightfield microscopy which uses a spectrally agile light source. The latter has a number of advantages over previous techniques.

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