http://www2.mae.ufl.edu/nkim/Papers/paper70.pdf

Practical options for selecting data-driven or physics-based prognostics algorithms with reviews

Different types of machines having rotary component are linked together in process industries, to perform the process of manufacturing. The failure of any single machine rotary component in the process can result in loss of money per downtime hour. To continue the working of the machines, it is necessary to monitor the health of the machine during its operation. Bearing failure is considered to be one of the major causes of breakdown in different rotating machines operating in industry at high and low speeds. Vibration in machines is generated due to defective bearings. During use, the condition of the bearings change, hence the vibrations also change and its characteristic basically depends on the cause. Hence, this characteristic feature of the bearing makes it suitable for vibration monitoring and other monitoring techniques. This article presents the brief review of recent trends in research on bearing defects, sources of vibration and vibration measurement techniques in the time domain, frequency domain and time frequency domain. The study reveals that, the envelope analysis method and time–frequency analysis technique are able to detect the bearing fault effectively. The wavelet analysis technique along with artificial neural network and fuzzy logic is also found to be the most effective techniques for fault analysis in rolling element bearing. Finally, it is concluded that vibration analysis technique along with other condition monitoring techniques gives better results in the fault diagnostics and condition monitoring of rolling element bearing.

Review of Condition Monitoring of Rolling Element Bearing Using Vibration Analysis and Other Techniques

http://www.scielo.org.mx/pdf/jart/v12n3/v12n3a5.pdf

Vibration Analysis of Rolling Element Bearings Defects

Unsupervised domain adaptation (UDA)-based methods have made great progress in bearing fault diagnosis under variable working conditions. However, most existing UDA-based methods focus only on minimizing the discrepancy of two working conditions. The similarity of fault features extracted from the bearing vibration signal is ignored. The samples near the distribution boundaries learned by the network might be misclassified. As a result, even if the marginal distributions is aligned well, the diagnosis result may not be satisfactorily. Therefore, this paper proposes a domain adaptation network base on contrastive learning (DACL) to achieve the aim of bearing fault diagnosis cross different working conditions and reduce the probability of samples being classified near or on the boundary of each class to improve diagnosis accuracy. The method is made up of a feature mining module and an adversarial domain adaptation module. In the feature mining module, a one-dimensional Convolutional Neural Network (1-D CNN) is utilized to extract features from raw vibration signals. The adversarial domain adaptation module followed is designed to learn domain-shared discriminant features for aligning marginal distribution. Meanwhile, the contrastive estimation term is designed to quantize the similarity of data distribution and increase the distance between samples of different health conditions, declining the probability of samples near the boundary and improving diagnosis performance. At last, an adaptive factor is introduced to measure the relative importance of transferring and discriminating abilities of the method. The effectiveness of the proposed method is confirmed by examining various fault diagnosis scenarios with domain discrepancies across the source and target domains, using experimental data from two bearing systems. 

Domain adaptation network base on contrastive learning for bearings fault diagnosis under variable working conditions

Recently it was proposed that voids in crystals could grow by emission of shear dislocation loops [V.A. Lubarda, M.S. Scheider, D.H. Kalantar, B.A. Remington, M.A. Meyers, Acta Materialia 52 (2004) 1397–1408]. Even more recently, this proposal was ostensibly supported by molecular simulations of voids in strained single crystals [S. Traiviratana, E.M. Bringa, D.J. Benson, M.A. Meyers, Acta Materialia 56 (2008) 3874–3886]. The purpose of this comment is to dispute this recent assertion as unfounded.

Shear impossibility - Comments on "Void growth by dislocation emission" and "Void growth in metals: atomistic calculations"

Element bearing is one of the widely used universal parts in machine. Its running condition and failure rate influence the performance, service life and efficiency of the equipment directly. So it is significant to research on bearing condition monitoring and fault diagnosis techniques. The paper describes the use of vibration measurements by a periodic monitoring system for monitoring the condition of rolling element bearing of the centrifugal machine. Vibration data is collected using accelerometers, which are placed at the 12 o’clock position at both the drive end and the driven end of the centrifugal machine. Vibration signals are collected using a 16 channel DAT recorder, and are post processed by vibration signals analysis software in personal computer. Simple diagnosis by vibration is based on frequency analysis. Each element of rolling bearing is of its fault characteristic frequency. This paper introduces frequency analysis method of using low and high frequency bands in conjunction with time domain waveform. Fault position of drive end bearing in the centrifugal machine is detected successfully by using this method.

Fault Diagnosis of Rolling Element Bearing Based on Vibration Frequency Analysis

In order to acquire flow characteristics in hot plastic deformation and establish the optimum hot formation processing parameters for 7055 aluminum alloy, the hot compressive flow stress behavior was studied at the temperatures from 300 to 450 ℃ and strain rates from 0.01 to 10s -1 on Gleeble-3180 thermo-simulation machine. The stress exponent and activation energy were acquired with successive approximation method by regression analysis. On the basis of the relationship between other deformation parameters and strain by polynomial fitting, constitutive equation consisting of temperature, strain rate and strain was established. The results show that 7055 aluminum alloy is positive strain rate sensitive material and the flow stress increases with the increase of strain rate and decreases with the increase of temperature. The experimental results agree with the predictive values according to the constitutive equation. DOI: http://dx.doi.org/10.5755/j01.mech.22.5.12527

https://mechanika.ktu.lt/index.php/Mech/article/download/12527/8220

Flow stress behavior and constitutive model of 7055 aluminum alloy during hot plastic deformation

In order to study the temperature distribution of aluminum alloy thick plate during snake hot rolling, several coupled thermo-mechanical models using finite element method (FEM) were established. Effects of different factors on temperature distribution of the plate and the bending behavior due to temperature difference were analyzed. Temperature asymmetry coefficient was defined in this study. The results show that the temperature distribution of plate is asymmetrical and the temperature of the lower surface is higher than the upper surface during snake hot rolling, in which the maximum α can gd reach 58 °C/m. The asymmetric coefficient was increased with the increase of rolling velocity and speed ratio. Different ways of heat exchange play different roles in the temperature distribution. Friction heat and deformation heat play dominant role in hot rolling process and pass interval time and their weight influences were 47 and 69 %, respectively. The bending curvature is increased with the increase of temperature difference and pass reduction and decreased dramatically with the increase of initial thickness. The FEM results agree well with experimental results.

Analysis of temperature asymmetry of aluminum alloy thick plate during snake hot rolling

An experiment study of temperature parameter on bonding process and bonding quality in thermosonic wire bonding was performed in this paper The experiment method was based on changing regularly bonding temperature and gaining the bonding strength by shearing gold ball joint by a high precision gauge The experiment results and analysis can find out the relationship of bonding temperature and bonding strength, and get the temperature ultimate, favorite temperature window and bondability window at that bonding condition Moreover, the experiment can find that the effect of temperature on impedance and power of PZT transducer in bonding process These experiment phenomena and analysis results can be help to research on bonding parameters matching and optimization in thermosonic wire bonding

Experiment study of temperature parameter effect on bonding process and quality in thermosonic wire bonding

In order to obtain the maximum driving forces of hydraulic cylinders in the process of boom design, the solid model was built in Pro/E and then imported into ADAMS where the dynamic simulation model was established. Processes of the boom transforming from horizontal to typical poses were simulated and driving force variation curves of the hydraulic cylinders were generated. According to the results, location of the joint connecting cylinder 2 and the links was optimized in ADAMS and the driving force decreased as a result. It is instructive to structure design of boom.

Simulation and Optimization of the Driving Forces of Hydraulic Cylinders for Boom of Truck Mounted Concrete Pump

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