scholarly journals Roller Bearing Monitoring by New Subspace-Based Damage Indicator

2015 ◽  
Vol 2015 ◽  
pp. 1-11
Author(s):  
G. Gautier ◽  
R. Serra ◽  
J.-M. Mencik

A frequency-band subspace-based damage identification method for fault diagnosis in roller bearings is presented. Subspace-based damage indicators are obtained by filtering the vibration data in the frequency range where damage is likely to occur, that is, around the bearing characteristic frequencies. The proposed method is validated by considering simulated data of a damaged bearing. Also, an experimental case is considered which focuses on collecting the vibration data issued from a run-to-failure test. It is shown that the proposed method can detect bearing defects and, as such, it appears to be an efficient tool for diagnosis purpose.

2014 ◽  
Vol 592-594 ◽  
pp. 2081-2085 ◽  
Author(s):  
Bharadwaj Nanda ◽  
Aditi Majumdar ◽  
Damodar Maity ◽  
Dipak K. Maiti

A simple and robust methodology is presented to identify damages in a structure using changes in vibration data. A comparison is made among damage indicators such as natural frequencies, mode shape data, curvature damage factors and flexibility matrices to study their efficacy in damage assessment. Continuous ant colony optimization (ACOR) technique is used to solve the inverse problem related to damage identification. The outcome of the simulated results demonstrates that the flexibility matrix as a damage indicator provides better damage identification.


2021 ◽  
Vol 15 (58) ◽  
pp. 416-433
Author(s):  
Samir Khatir ◽  
Magd Abdel Wahab ◽  
Samir Tiachacht ◽  
Cuong Le Thanh ◽  
Roberto Capozucca ◽  
...  

Metaheuristic algorithms have known vast development in recent years. And their applicability in engineering projects is constantly growing; however, their deferent exploration and exploitation techniques cause the engineering problems to favor some algorithms over others. This paper studies damage identification in steel plates using Frequency Response Function (FRF) damage indicator to detect and localize the healthy and damaged structure. The study is formulated as an inverse analysis, investigating the performance of three new metaheuristic algorithms of Wild Horse Optimizer (WHO), Harris Hawks Optimization (HHO), and Arithmetic Optimization Algorithm (AOA).  The objective function is based on measured and calculated FRF damage indicators. The results showed that the case of four damages with different damage severity levels presented a good challenge where the HWO algorithm was shown to have the best performance.  Both in convergence speed and CPU time.


BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Xiujin Li ◽  
Hailiang Song ◽  
Zhe Zhang ◽  
Yunmao Huang ◽  
Qin Zhang ◽  
...  

Abstract Background With the emphasis on analysing genotype-by-environment interactions within the framework of genomic selection and genome-wide association analysis, there is an increasing demand for reliable tools that can be used to simulate large-scale genomic data in order to assess related approaches. Results We proposed a theory to simulate large-scale genomic data on genotype-by-environment interactions and added this new function to our developed tool GPOPSIM. Additionally, a simulated threshold trait with large-scale genomic data was also added. The validation of the simulated data indicated that GPOSPIM2.0 is an efficient tool for mimicking the phenotypic data of quantitative traits, threshold traits, and genetically correlated traits with large-scale genomic data while taking genotype-by-environment interactions into account. Conclusions This tool is useful for assessing genotype-by-environment interactions and threshold traits methods.


2009 ◽  
Vol 24 (3) ◽  
pp. 153-159 ◽  
Author(s):  
Q. W. Yang

Structural damage identification using ambient vibration modes has become a very important research area in recent years. The main issue surrounding the use of ambient vibration modes is the mass normalization of the measured mode shapes. This paper presents a promising approach that extends the flexibility sensitivity technique to tackle the ambient vibration case. By introducing the mass normalization factors, manipulating the flexibility sensitivity equation, the unknown damage parameters and mass normalization factors can be computed simultaneously by the least-square technique. The effectiveness of the proposed method is illustrated using simulated data with measurement noise on three examples. It has been shown that the proposed procedure is simple to implement and may be useful for structural damage identification under ambient vibration case.


2019 ◽  
Vol 24 (3) ◽  
pp. 467-475
Author(s):  
Mohamed El Morsy ◽  
Gabriela Achtenova

The present article’s intent is to measure and identify the roller bearing inner race defect width and its corresponding characteristic frequency based on filtered time-domain vibration signal. In case localized fault occurs in a bearing, the rolling elements encounter some slippage as the rolling elements enter and leave the bearing load zone. As a consequence, the incidence of the impacts never reproduce exactly at the same position from one cycle to another. Moreover, when the position of the defect is moving with respect to the load distribution zone of the bearing, the series of impulses are modulated in amplitude in time-domain and the conforming Bearing Characteristic Frequencies (BCFs) arise in frequency domain. In order to verify the ability of time-domain in measuring the fault of rolling bearing, an artificial fault is introduced in the vehicle gearbox bearing: an orthogonal placed groove on the inner race with the initial width of 0.6mm approximately. The faulted bearing is a roller bearing quantification of the characteristic features relevant to the inner race bearing defect. It is located on the gearbox input shaft—on the clutch side. To jettison the frequency associated with interferential vibrations, the vibration signal is filtered with a band-pass filter based on an optimal daughter Morlet wavelet function whose parameters are optimized based on maximum Kurtosis (Kurt.). The residual signal is performed for the measurement of defect width. The proposed technique is used to analyse the experimental signal of vehicle gearbox rolling bearing. The experimental test stand is equipped with two dynamometer machines; the input dynamometer serves as an internal combustion engine, the output dynamometer introduces the load on the flange of the output joint shaft. The Kurtosis and Pulse Indicator (PI) are selected as the evaluation parameters of the de-noising effect. The results show the reliability of the proposed approach for identification and quantification of the characteristic features relevant to the inner race bearing defect.


2020 ◽  
pp. 107754632093374
Author(s):  
Mehdi Fathalizadeh Najib ◽  
Ali Salehzadeh Nobari

Super-harmonic components in response to the harmonic excitation are sensitive indicators of damages such as breathing cracks in beams or kissing bonds in adhesive joints. In a model-based damage identification process using pattern recognition, these damage indicators can be extracted from the finite element model for all probable damage cases using stepped-sine simulation that necessitates nonlinear transient dynamic analysis with high computational costs. In this study, a procedure based on nonlinear autoregressive with exogenous input model is introduced as an alternative shortcut method for extraction of the damage indicators. As a case study, the finite element model of a beam connected to a rigid support via a flexible adhesive layer was used to investigate the efficiency of the proposed method. Kissing bond was introduced to the model as the source of nonlinearity via contact elements. The results prove that the super-harmonic components of orders up to 3, extracted from the nonlinear autoregressive with exogenous input model, agreed well with those extracted directly from the finite element model, whereas the computational time is reduced by a factor of 1/5. Consequently, the proposed method is very advantageous in the stage of damage pattern database creation in a real-world model-based damage identification process based on pattern recognition.


Author(s):  
Zhuang Li ◽  
Lei Jin ◽  
Ning Zhang ◽  
Yang Zhou

Cracks and voids are common defects in rotating systems and are a precursor to fatigue-induced failure. The application of statistical analysis, as a tool for damage identification and health monitoring in rotating machinery, is investigated. Experimental vibration data were collected for a set of health and cracked shafts. Formal statistical models have been proposed to describe the relationship between the vibration signals and the existence of damage. Damage detection and diagnosis are implemented based on statistical estimation and hypothesis testing. Such a statistical model provides a screening technique to detect other damage types. As a result, the proposed methods can improve the power of damage detection.


2015 ◽  
Vol 787 ◽  
pp. 927-931
Author(s):  
Mouleeswaran Senthilkumar ◽  
M. Yuvaraja ◽  
M. Kok

Centrifugal pumps are widely used in industry and also domestically. It is commonly used for its robust design and its efficiency. Every machine has to be monitored periodically in order to maintain its efficiency and also to avoid unexpected failure which lead to loss of efficiency. So fault diagnosis is necessary to monitor the pump periodically for finding out the defects in pump and to replace it if necessary. Dismantling and assembling of pumps during fault diagnosis is a tedious process, vibration analysis can be helpful to monitor the performance of the pump system without dismantling. For the experimentation purpose mono-block centrifugal pumps have been used in this work. By using the Lab VIEW program and DAQ card as an interface, amplitude and frequency of vibration is obtained at different axes of the pump with the help of an accelerometer. Then the vibration spectrum is analyzed and defects are pointed out by identifying the frequency at which the amplitude of vibration is above the danger limit. The defects such as unbalance of impeller, bent shaft in pump, misalignment of shaft, hydraulic pulsation, cavitation and bearing defects are diagnosed using vibration data. The frequency at which different defects are occurring has been founded out by means of experimentation in the centrifugal pumps. Thus by diagnosing centrifugal pump using vibration data reduces cost and time for periodical maintenance. Shape memory alloy based ATDVA is used to control the amplitude of vibration due to hydraulic pulsation. Around 60% reduction in amplitude of vibration is evident for the varying excitation frequency between 336 Hz and 340 Hz due to hydraulic pulsation.


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