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.

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

2017 ◽  
Vol 140 (1) ◽  
Author(s):  
Konstantinos Gryllias ◽  
Simona Moschini ◽  
Jerome Antoni
Keyword(s):  
Frequency Domain ◽  
Condition Monitoring ◽  
Health Monitoring ◽  
Aircraft Engine ◽  
Rotating Machinery ◽  
Operating Conditions ◽  
Vibration Monitoring ◽  
Diagnostic Features ◽  
Time Frequency ◽  
Acceleration Signal

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 cyclo-stationary, which is a particular class of nonstationary stochastic processes. 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 cyclo-stationarity (ICNS) in order to cover the speed-varying conditions. The effectiveness of the approach is evaluated on an acceleration signal captured on the casing of an aircraft engine gearbox, provided by SAFRAN.

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.

Application of Virtual Instrument on Condition Monitoring and Fault Diagnosis System of the Rotating Machinery

2012 ◽  
Vol 542-543 ◽  
pp. 161-164
Author(s):  
Yong Ying Du ◽  
Yu Ning Wang ◽  
Ming Ang Yin
Keyword(s):  
Fault Diagnosis ◽  
Data Acquisition ◽  
Frequency Domain ◽  
Condition Monitoring ◽  
Domain Analysis ◽  
Frequency Domain Analysis ◽  
Rotating Machinery ◽  
Waveform Data ◽  
Time Frequency ◽  
Acceleration Sensors

In the paper it can be easier to realize the acquisition of the rotating machinery vibration signal and condition monitoring through the configuration the platform of virtual instrumentation. For the data acquisition it is enough to be plus with two acceleration sensors and a counter. The system is divided into parameter setting module, data acquisition, storage and display module, amplitude domain analysis module, time-domain analysis module, frequency domain analysis module, time-frequency domain analysis module and fault diagnosis module. The signal acquisition is got by using the PCI-6024E data acquisition card. And it is can be saved as binary data stream files and waveform data file according to the requirements of the sequence data processing. Signal analysis is conducted by using LabVIEW software and draw out the vibration spectrum diagram in order to achieve fault diagnosis of rotating machinery.

Novel Joint Time Frequency Vibration Diagnostics of Turbine Engine Accessories

2010 ◽  
Author(s):  
Matthew J. Watson ◽  
Jeremy S. Sheldon ◽  
Hyungdae Lee ◽  
Carl S. Byington ◽  
Alireza Behbahani
Keyword(s):  
Frequency Domain ◽  
Gas Turbine ◽  
Health Monitoring ◽  
Health Management ◽  
Operating Conditions ◽  
Vibration Diagnostics ◽  
Turbine Engine ◽  
Time Frequency ◽  
Engine Components ◽  
Highly Loaded

Traditional engine health management development has focused on major gas turbine engine components (i.e., disks, blades, bearings, etc.) due to the fact that these components are expensive to maintain and their failures frequently have safety implications. However, the majority of events that lead to standing down of aircraft arise from gas turbine accessory components such as pumps, generators, auxiliary power units, and motors. Common vibration diagnostics, which are based on frequency domain analysis that assumes the monitored signal is “stationary” during the analysis period, are not effective for these components. This is true because operating conditions are often non-stationary and evolving, which leads to spectral smearing and erroneous analysis that can cause missed detections and false alarms. Traditionally, this is avoided by defining steady state operating conditions in which to perform the analysis. Although this may be acceptable for major engine components, which are typically highly loaded during normal steady operation, many engine accessories are only high loaded during transients, especially startup. For example, an engine starter or fuel pump may be more highly loaded and therefore susceptible to damage during engine start up, typically avoided by traditional vibration analysis methods. More importantly, certain component faults and their progression can also lead to non-stationary vibration signals that, because of the smearing they induced, would be missed by traditional techniques. As a result, the authors have developed a novel engine accessory health monitoring methodology that is applicable during non-stationary operation through application of joint time-frequency analysis (JTFA). These JTFA approaches have been proven in other disciplines, such as speech analysis, radar processing, telecommunications, and structural analysis, but not yet readily applied to engine accessory component diagnostics. This paper will highlight the results obtained from applying JTFA techniques, including Short-Time Fourier Transform, Choi-Williams Distribution, Continuous Wavelet Transform, and Time-Frequency Domain Averaging, to very high frequency (VHF) vibration data collected from healthy and damaged turbine engine accessory components. The resulting accuracy of the various approaches were then evaluated and compared with conventional signal processing techniques. As expected, the JTFA approaches significantly outperformed the conventional methods. On-board application of these techniques will increase prognostics and health management (PHM) coverage and effectiveness by allowing accessory health monitoring during the most life influencing regimes regardless of operating speed and reducing inspection and replacement costs resulting in minimizing the vehicle down time.

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.

scholarly journals Improvement of Intake Structures in a Two-Way Pumping Station with Experimental Analysis

2020 ◽  
Vol 10 (19) ◽  
pp. 6842
Author(s):  
Yanjun Li ◽  
Rong Lu ◽  
Huiyan Zhang ◽  
Fanjie Deng ◽  
Jianping Yuan
Keyword(s):  
Frequency Domain ◽  
Great Influence ◽  
Operating Conditions ◽  
Stable Operation ◽  
Pressure Pulsations ◽  
Pump Unit ◽  
Measuring Point ◽  
Time Frequency ◽  
Pumping Station ◽  
Bell Mouth

Pumping stations are important regulation facilities in a water distribution system. Intake structures can generally have a great influence on the operational state of the pumping station. To analyze the effects of the bell mouth height of the two-way intake on the performance characteristics and the pressure pulsations of a two-way pumping station, the laboratory-sized model pump units with three different intakes were experimentally investigated. To facilitate parameterized control, ellipse and straight lines were used to construct the profile of the bell mouth. The frequency domain and time-frequency domain of the pressure pulsations on the wall of intakes were analyzed by the Welch’s power spectral density estimate and the continuous wavelet transform (CWT) methods, respectively. The results showed that the bell mouth height (H) has significant influences on the uniformity of the impeller inflow and the operation stability of the pump unit. When H = 204 mm, the data fluctuated greatly throughout the test process and the performance curves are slightly lower than the other two schemes. As the bell mouth height gradually decreases, the average pressure difference of each measuring point began to decrease, more homogeneous velocity distribution of impeller inflow can be ensured. The amplitude of blade passing frequency is obvious in the spectrum. While when (H) is more than 164 mm, the main frequency of pressure pulsations at three points fluctuates with the rotation of the impeller. When H decreases to 142 mm, pressure pulsations will be independent of the operating conditions and positions which contributes to the long-term stable operation of the pump unit.

Class-information–incorporated kernel entropy component analysis with application to bearing fault diagnosis

2020 ◽  
pp. 107754632093203
Author(s):  
Hongdi Zhou ◽  
Fei Zhong ◽  
Tielin Shi ◽  
Wuxing Lai ◽  
Jian Duan ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Frequency Domain ◽  
Hebbian Learning ◽  
Component Analysis ◽  
Operating Conditions ◽  
Time Frequency ◽  
Bearing Fault ◽  
Bearing Fault Diagnosis ◽  
Class Information ◽  
Entropy Component

Rolling bearings are present ubiquitously in industrial fields; timely fault diagnosis is of crucial significance in avoiding serious catastrophe. The extraction of ideal fault feature is a challenging task in vibration-based bearing fault detection. In this article, a novel method called class-information–incorporated kernel entropy component analysis is proposed for bearing fault diagnosis. The method is developed based on the Hebbian learning theory of neural network and the kernel entropy component analysis which attempts to compress the most Renyi quadratic entropy of input dataset after dimension reduction and presents a good performance for nonlinear feature extraction. Class-information–incorporated kernel entropy component analysis can take advantage of the label information of training samples to guide dimensional reduction and still follow the same simple mathematical formulation as kernel entropy component analysis. The high-dimensional feature dataset including time-domain, frequency-domain, and time–frequency domain characteristic parameters is first derived from the vibration signals. Then, the intrinsic geometric features are extracted by class-information–incorporated kernel entropy component analysis, and a classification strategy based on fusion information is applied to recognize different operating conditions of bearings. The experimental results demonstrated the feasibility and effectiveness of the proposed method.

A Computationally Efficient Multichannel Active Road Noise Control System

2014 ◽  
Vol 137 (1) ◽  
Author(s):  
Jie Duan ◽  
Mingfeng Li ◽  
Teik C. Lim ◽  
Ming-Ran Lee ◽  
Ming-Te Cheng ◽  
...  
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
Noise Control ◽  
Acoustic Noise ◽  
Reference Signal ◽  
Active Noise Control ◽  
Computational Cost ◽  
Road Noise ◽  
Time Frequency ◽  
Fxlms Algorithm

A multichannel active noise control (ANC) system has been developed for a vehicle application, which employs loudspeakers to reduce the low-frequency road noise. Six accelerometers were attached to the vehicle structure to provide the reference signal for the feedforward control strategy, and two loudspeakers and two microphones were applied to attenuate acoustic noise near the headrest of the driver's seat. To avoid large computational burden caused by the conventional time-domain filtered-x least mean square (FXLMS) algorithm, a time-frequency domain FXLMS (TF-FXLMS) algorithm is proposed. The proposed algorithm calculates the gradient estimate and filtered reference signal in the frequency domain to reduce the computational requirement, while also updates the control signals in the time domain to avoid delay. A comprehensive computational complexity analysis is conducted to demonstrate that the proposed algorithm requires significantly lower computational cost as compared to the conventional FXLMS algorithm.

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