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Go to Editorial ManagerVibration in rotating machines and structures is normally measured using accelerometers and other vibration sensors. For large machines and structures, the process of collecting vibration data is tedious and time-consuming due to the large number of points where vibration data must be measured. In this paper, a novel non-contact vibration measurement method has been introduced by using a high-speed camera as a vibration measurement device. This method has many advantages compared with the others. It has a low cost, easy to setup, and high automation. It also can be used for full-field measurement. Many tests have been accomplished to prove the validation of this method. The verification test has been accomplished by using the machinery faults simulator. It presented a reasonable validation that the operation deflection shapes (ODS) and the phase difference of any object can be successfully measured by using a high-speed camera. The mode shape tests have been accomplished by using the whirling of shaft apparatus device to extract the time domain, frequency domain, ODS, and phase differences for many points on the shaft at the first two critical speeds. The results proved that the high-speed camera can be used to detect the vibration signal in many different fault cases. It also proved that the high-speed camera can be used to detect the ODS and the phase angle difference. That gives the proposed method more robust and acceptance.
In this work, the efficiency of double Gauss quadrature method, used to integrate over a rectangular element in 3D BEM, has been investigated. The efficiency of a quadrature or integration scheme is investigated by estimating the critical ratio for which the absolute relative error of the numerical integration is less than $1\times10^{-6}$. As small as the critical ratio is, the quadrature is more efficient. Also, special transformation techniques have been introduced and used to increase the accuracy and efficiency of double Gauss quadrature especially for near singular cases, where the source point is very close to the element under consideration. Three types of kernels were considered, weak, strong and hyper singular kernels which can be encountered in the integral equation of 3D elastodynamics BEM problems.
A method based on experimentally calibrated rotor model is proposed in this work for unbalance identification of flexible rotors without trial runs. Influence coefficient balancing method especially when applied to flexible rotors is disadvantaged by its low efficiency and lengthy procedure, whilst the proposed method has the advantage of being efficient, applicable to multi-operating spin speeds and do not need trial runs. An accurate model for the rotor and its supports based on rotordynamics and finite elements analysis combined with experimental modal analysis, is produced to identify the unbalance distribution on the rotor. To create digital model of the rotor, frequency response functions (FRFs) are determined from excitation and response data, and then modal parameters (natural frequencies and mode shapes) are extracted and compared with experimental analogies. Unbalance response is measured traditionally on rotor supports, in this work the response measured from rotating disks instead. The obtained results show that the proposed approach provides an effective alternative in rotor balancing. Increasing the number of balancing disks on balancing quality is investigated as well.
The dieless drawing process is an innovative method emanated and appeared in coincidence with development of the concept of metal superplasticity. It is utilized from the local heating of a wire or tube to a specified temperature and followed by a local cooling, so an additional deformation is inhibited. In this study, a special dieless drawing machine was designed to carry out an experimental program on SUS304-stainless steel wire having diameter of (1.6-2) mm to investigate the main process parameters such as speeds, heat quantity, heating coil width and heating-cooling separation distance. Also, a numerical model based on thermo-mechanical analysis was developed and validated with experimental program. Furthermore, an artificial neural network ANN model based on current experimental data was prepared to predict the dieless drawing behavior. A maximum area reduction of 40.7% was obtained in single pass. A 3.12mm/s feeding velocity and 4.97mm/s drawing velocity were realized through the experimental tests. The results showed that both drawing force and wire profile were effected by increasing of feeding speed, heating coil width and separation distance. Also, it is confirmed that strain rate was reduced by increasing the heating coil width and the reduction ratio was promoted. A maximum error of 21% was recorded between ANN model and experimental results. The results showed a good agreement among experimental, numerical and ANN models.
Bearing fault diagnosis is essential for the maintenance, durability, and reliability of rotating machines. It can minimize economic losses by removing unplanned downtime in the industry due to the failure of rotary machines. In bearing fault detection, developing fault features extraction techniques that can successfully applicable for various fault severity and different operating conditions is still a critical issue. In the current work, the feature extraction technique is a combination between pre-processing algorithms and envelope analysis method. In the pre- processing stage, the autoregressive (AR) model is used to filter the original signal and remove the deterministic vibration sources, as well as maintain the signal representing the condition of the bearing without contaminating noises. Then, the most suitable frequency band is selected based on the spectral kurtosis (SK) analysis. This band contains the signature frequencies of the roller bearing. After that, envelope analysis is employed for detecting faults at different severity. Finally, the features represented the peaks at fundamental fault frequencies are automatically selected from the envelope spectrum. By analyzing all diagnoses results, it is found that the presented method effectively extracts the features at calculated resonance bearing frequencies and proves the significance of the enhancements in a pre-filtering stage in the overall detection performance. Also, it can benefit from these features in the fault classification fields at different speeds because it is independent of speed variation.
The rotor unbalances and misalignment in rotary machines are two major sources of vibration. rotor unbalance and misalignment is omnipresent in all rotating machinery widely used in many industrial applications, posing a serious threat to machine life and operation. The present work is an attempt to investigate the vibration characteristics (Amplitude, FFT, and time waveform) of a rotating mechanical system, which has an unbalanced rotor and misalignment. Vibration signals are acquired using an accelerometer mounted on the bearing housing nearer to the rotor. The FFT analysis of the acquired data revealed the response of an unbalanced rotor under operating conditions. Numerical analysis of the system using ANSYS portrayed the modal frequencies and mode shapes. Transient Structural analysis illustrates the response of the system to different mass unbalances. The results revealed that the magnitude of vibration characteristics significantly increases with excitation frequency and exciting force.