scholarly journals Condition monitoring of PARR-1 rotating machines by vibration analysis technique

2014 ◽  
Vol 29 (3) ◽  
pp. 249-252 ◽  
Author(s):  
Javed Qadir ◽  
Hameed Qaiser ◽  
Mehar Ali ◽  
Masood Iqbal
Keyword(s):  
Condition Monitoring ◽  
Preventive Maintenance ◽  
Vibration Analysis ◽  
Research Reactor ◽  
Vibration Spectrum ◽  
Experimental Setup ◽  
Performance Parameters ◽  
Vibration Data ◽  
Analysis Technique ◽  
Vibration Signatures

Vibration analysis is a key tool for preventive maintenance involving the trending and analysis of machinery performance parameters to detect and identify developing problems before failure and extensive damage can occur. A lab-based experimental setup has been established for obtaining fault-free and fault condition data. After this analysis, primary and secondary motor and pump vibration data of the Pakistan Research Reactor-1 were obtained and analyzed. Vibration signatures were acquired in horizontal, vertical, and axial directions. The 48 vibration signatures have been analyzed to assess the operational status of motors and pumps. The vibration spectrum has been recorded for a 2000 Hz frequency span with a 3200 lines resolution. The data collected should be helpful in future Pakistan Research Reactor-1 condition monitoring.

The Condition Monitoring of Rolling Element Bearings Using Vibration Analysis

1984 ◽  
Vol 106 (3) ◽  
pp. 447-453 ◽  
Author(s):  
J. Mathew ◽  
R. J. Alfredson
Keyword(s):  
Condition Monitoring ◽  
Sufficient Evidence ◽  
Rolling Element Bearings ◽  
Bearing Failure ◽  
Machine Condition ◽  
Vibration Data ◽  
Machine Condition Monitoring ◽  
Rolling Element ◽  
Vibration Signatures ◽  
Bearing Damage

A brief review on techniques of machine condition monitoring is presented followed by a description and results of a study involving the monitoring of vibration signatures of several rolling element bearings with a view to detecting incipient failure. The vibration data were analyzed and several parameters were assessed with regard to their effectiveness in the detection of bearing condition. It was found that all the parameters were of some value depending on the type of bearing failure encountered. Generally, frequency domain parameters were more consistent in the detection of damage than time domain parameters. However, sufficient evidence is produced to show that it would be unreliable to depend exclusively on any one technique to detect bearing damage.

Vibration fault identification of a turbojet engine based on cepstrum analysis

2021 ◽  
pp. 095441002110477
Author(s):  
Jingjing Huang ◽  
Xijun Zhang
Keyword(s):  
Vibration Analysis ◽  
Frequency Component ◽  
Fault Identification ◽  
Complex Signals ◽  
Vibration Data ◽  
Engine Vibration ◽  
Cepstrum Analysis ◽  
Turbojet Engine ◽  
Analysis Technique ◽  
Periodic Components

A vibration fault identification method based on vibration state characteristics of a turbojet engine and cepstrum analysis technology was proposed in this paper, and the application of cepstrum in vibration analysis of an aero-engine was also discussed. The vibration data of the turbojet engine in three different test cases of 0.8 rated state, max power state, and afterburning state were analyzed using the cepstrum analysis method. The periodic components and the characteristics of multi-component side-frequency complex signals in the dense overtone vibration signals were separated and extracted, which reflected the sensitivity of the positions of the compressor casing and the turbine casing to the harmonic vibration components of high- and low-pressure rotors and the characteristic difference of different vibration parts. Thus, effective identification of vibration faults was achieved. The results shows that the cepstrum analysis technique applied to the vibration analysis of the turbojet engine can better identify the sideband components of the frequency domain modulated signal and enhance the recognition capability of the fault frequency component, which is helpful to identify the engine vibration fault quickly and accurately.

Testing for detection of crack in rotor using vibration analysis: an experimental approach

2019 ◽  
Vol 36 (6) ◽  
pp. 999-1013
Author(s):  
Bhumi Ankit Shah ◽  
Dipak P. Vakharia
Keyword(s):  
Condition Monitoring ◽  
Vibration Analysis ◽  
Critical Speed ◽  
Energy Analysis ◽  
Wavelet Packet ◽  
Rotating Machinery ◽  
Wavelet Packets ◽  
Energy Component ◽  
Content Type ◽  
Analysis Technique

Purpose Many incidents of rotor failures are reported due to the development and propagation of the crack. Condition monitoring is adopted for the identification of symptoms of the crack at very early stage in the rotating machinery. Identification requires a reliable and accurate vibration analysis technique for achieving the objective of the study. The purpose of this paper is to detect the crack in the rotating machinery by measuring vibration parameters at different measurement locations. Design/methodology/approach Two different types of cracks were simulated in these experiments. Experiments were conducted using healthy shaft, crack simulated shaft and glued shaft with and without added unbalance to observe the changes in vibration pattern, magnitude and phase. Deviation in vibration response allows the identification of crack and its location. Initial data were acquired in the form of time waveform. Run-up and coast-down measurements were taken to find the critical speed. The wavelet packet energy analysis technique was used to get better localization in time and frequency zone. Findings The presence of crack changes the dynamic behavior of the rotor. 1× and 2× harmonic components for steady-state test and critical speed for transient test are important parameters in condition monitoring to detect the crack. To separate the 1× and 2× harmonic component in the different wavelet packets, original signal is decomposed in nine levels. Wavelet packet energy analysis is carried out to find the intensity of the signal due to simulated crack. Originality/value Original signals obtained from the experiment test set up may contain noise component and dominant frequency components other than the crack. Wavelet packets contain the crack-related information that are identified and separated in this study. This technique develops the condition monitoring procedure more specific about the type of the fault and accurate due to the separation of specific fault features in different wavelet packets. From the experiment end results, it is found that there is significant rise in a 2× energy component due to crack in the shaft. The intensity of a 1× energy component depends upon the shaft crack and unbalance orientation angle.

A Composite Vibration Spectrum for a Machine for Vibration Based Condition Monitoring

2012 ◽  
Author(s):  
Keri Ali Elbhbah ◽  
Jyoti K. Sinha
Keyword(s):  
Condition Monitoring ◽  
Research Study ◽  
Vibration Spectrum ◽  
Vibration Measurement ◽  
Test Rig ◽  
Data Set ◽  
Composite Spectrum ◽  
Vibration Data ◽  
Rotating Machine ◽  
Machine Assembly

Vibration-based condition monitoring requires vibration measurement on each bearing pedestal and then signal processing for all the measured vibration data to identify fault(s), if any, in a rotating machine. Such a large vibration data set makes the diagnosis process complex generally for a large rotating machine supported through a number of bearing pedestals. Hence a new method is proposed in the present research study to construct a single composite spectrum using all the measured vibration data set. This composite spectrum is expected to represent the dynamics of the complete machine assembly and can make fault diagnosis process relatively easier and straightforward. The paper presents the concept of the proposed composite spectrum and the results when applied to a laboratory test rig with different simulated faults.

scholarly journals Optimal Preventive Maintenance of Wind Turbine Components with Imperfect Continuous Condition Monitoring

Energies ◽  
2019 ◽  
Vol 12 (19) ◽  
pp. 3801 ◽  
Author(s):  
Ahmed Raza ◽  
Vladimir Ulansky
Keyword(s):  
Wind Turbine ◽  
Condition Monitoring ◽  
Preventive Maintenance ◽  
False Negative ◽  
Maintenance Cost ◽  
Arbitrary Distribution ◽  
Average Lifetime ◽  
True Negative ◽  
Degradation Failure ◽  
Lifetime Maintenance

Among the different maintenance techniques applied to wind turbine (WT) components, online condition monitoring is probably the most promising technique. The maintenance models based on online condition monitoring have been examined in many studies. However, no study has considered preventive maintenance models with incorporated probabilities of correct and incorrect decisions made during continuous condition monitoring. This article presents a mathematical model of preventive maintenance, with imperfect continuous condition monitoring of the WT components. For the first time, the article introduces generalized expressions for calculating the interval probabilities of false positive, true positive, false negative, and true negative when continuously monitoring the condition of a WT component. Mathematical equations that allow for calculating the expected cost of maintenance per unit of time and the average lifetime maintenance cost are derived for an arbitrary distribution of time to degradation failure. A numerical example of WT blades maintenance illustrates that preventive maintenance with online condition monitoring reduces the average lifetime maintenance cost by 11.8 times, as compared to corrective maintenance, and by at least 4.2 and 2.6 times, compared with predetermined preventive maintenance for low and high crack initiation rates, respectively.

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