نشریه صوت و ارتعاش
پیاپی 24 (پاییز و زمستان 1402)

Laser Doppler vibrometers (LDV) are one of the most accurate measurement tools in which the basics of laser interferometry and the Doppler effect are used to measure the vibration characteristics of the objects. These devices are able to measure the vibration velocity from one per hundred of micrometers per second up to tens of meters per second with the highest accuracy. There are many arrangements of LDV, in each of them different analog or digital processors can be used to extract the signal. In this research, at first, the interference signal is simulated and the vibration speed was calculated using the zero-crossing counting method. Then, the single photodiode homodyne Michelson LDV arrangement was used experimentally with the help of analog and digital processes such as zero-crossing counting and moving averaging to measure and control the vibration speed of a speaker. The results showed that by applying a frequency of 17 Hz to the speaker, its vibration velocity was calculated in order of 1 μm/s. Moreover, before and after applying the moving average, the speaker speeds were compared and it was found that after removing the noise, the signals show the moving speed of the vibrating object more accurately.

Condition monitoring and fault diagnosis of large industrial equipment has become very important role nowadays. Powerful artificial intelligent methods can be appropriately used on big data without any further statistical assumption. In this research, two compromising methods including deep neural network and convolutional neural network have been used to classify faults of a laboratory gearbox. Both networks have been used to classify nine faulty classes and one healthy class of the gearbox using vibration signal. The data have been collected at six different load and speed combinations. The measured time domain vibration signal was used as neural network input. The classification accuracy of both methods have been obtained. The effect of challenging parameters such as window size, learning rate and number of extracted features on the classification accuracy have been studied. Finally after the comparison of the results, it was concluded that the accuracy of the convolutional neural network was superior.

Health monitoring and damage detection in structures is important for maintaining the safety and health of individuals as well as for dealing with economic losses. This article compares primary and secondary modal information, including the frequency values and vibration mode shapes, for health monitoring and damage detection in beams. The impact of the damage is observed as a difference between primary and secondary frequency values, as well as a difference between the coefficients of the polynomial curves. Also, the Pearson's Correlation Coefficient (PCC) between the primary and secondary modes is calculated as values other than 1 and -1 that indicate the impact of damage on the relative displacement of degrees of freedom. However, damage locations cannot be identified by curve fitting, correlation, and comparison of natural frequencies; thus, comparison of primary and secondary shapes of vibration modes was made based on determination of central curvature. It was shown that the difference between the primary and secondary curvature graphs occurs as fractures created in damaged positions and in the curvature graph of the secondary situation; hence, the damaged locations are identifiable.

Turbocharging is an auxiliary system that increases the output power and efficiency of internal combustion engines by injecting more air into the combustion chamber. Studying their dynamic behavior and knowing their critical speeds is important due to their widespread use in automobile engines, locomotives, and aerospace industries. In this research, first, an analytical model of 16 degrees of freedom is presented to calculate the natural frequencies of the turbocharger, and based on it, the governing equations are derived. Then, the results obtained from the analytical solution of the governing equations are validated using the finite element method. Next, the first to fourth critical speeds of the system are calculated at different distances of the bearings on the shaft and the Campbell diagram of the system is analyzed. Finally, the frequency response of the system due to the mass imbalance in different positions of the bearings is checked. The results show that by increasing the distance between the bearings, the first and second critical velocities of the system increase, and the amplitude of the system vibrations at the first resonance frequency decreases.

Phononic crystals are periodic composite materials that are formed by the alternating repetition of one (or more) inclusion in a host. Duo to their band gap characteristic and their ability to manage the propagation of elastic waves, many researches have been devoted to this subject in recent years. This article investigates the propagation of in-plane mode of elastic wave in alumina-epoxy composite. The effect of inclusion shape on composite band gap has been investigated by finite element method with the help of Comsol software. The lattice is assumed to be square. In order to verify the results, first, the band structure of phononic crystal with a circular inclusion shape was obtained and compared with that of plane wave expansion method and experimental results. Then, the band structure of phononic crystals with triangular, square, regular pentagonal, regular hexagonal, regular heptagonal, and regular octagonal inclusion shapes have been obtained. The obtained results showed that the band gap of the phononic crystal with the triangular inclusion shape (frequency range 47.3 to 66.1 and 79.9 to 90.3 kHz) is wider compared to other studied inclusion shapes.

In this study, the application of wavelet transform in the natural degradation of roller bearings based on the processing of acoustic emission signals has been investigated. In order to extract the bearing acoustic emission signals, a suitable laboratory arrangement and data collection equipment was used. The processing of acoustic emission signals in time-frequency domains was performed using wavelet transform analysis. In order to capturing the acoustic emission signals, three sensors namely Pico, R6α and WSα were applied. The results showed that the acoustic emission method is an efficient method for estimating the bearing natural degradation. In this study, to select the mother wavelet, the method of comparing the ratio of energy to converted signal entropy was used. Comparison of energy versus entropy for the 53 mother wavelets studied shows that the Bior 3.1 mother wavelet has the highest energy to Shannon entropy ratio and is selected as the best mother wavelet. Also, the performance analysis of the three sensors showed that all three sensors used are suitable for investigating the natural degradation of the bearing, however, the Pico sensor scored higher.

Passive acoustics has been recognized as an important strategy for long-term detection and monitoring of underwater gas leaks in natural sites or in underwater gas pipelines. The ability of an acoustic system to detect underwater gas leaks is primarily controlled by the signal-to-noise ratio (SNR) of bubble sounds. In the current research, it is tried to provide the possibility of detecting the leakage signal with low flow rate and in the presence of strong noise by using the CFAR method. In this regard, "Bellhop" software was used to model the underwater acoustic channel. According to previous researches, the minimum detectable leakage flow rate for the threshold-based detection method is equal to 2 liters per minute (at a maximum distance of 0.5 meters from the leakage location) and the SNR required by this method for detection is also equal to 6 dB. . Considering the lower power of the signal with low flow rate and as a result lower SNR compared to the high rate of leakage current, it is shown in the simulated scenario that by using the CFAR method, the acoustic signal of leakage with low flux can be detected. also identified On the other hand, the performance of the OS-CFAR method is much better than other methods, and it provides the possibility of detecting the leakage signal with low flux even at very low SNR values (up to SNR = -10 dB).

TitleA review of the performance parameters of magnetorheological vibration dampers.Abstract The development of magnetorheological vibration dampers with the aim of preventing the adverse effects of vibrations has attracted the attention of researchers and industrialists in recent years. From the point of view of physical structure, these dampers are usually divided into three categories: single pipe, double pipe and bilateral, which are used in different shear, pressure, flow and combined modes. Magnetorheological fluids are among smart magnetic materials that exhibit different rheological properties when exposed to a magnetic field compared to the state without the application of a magnetic field, and with the increase in coercivity, the applied magnetic field and the amount of force required to cause deformation in the fluid increases. Magnetorheological vibration dampers are used to reduce vibrations transmitted to car seats, smart brakes in knee prostheses, dampers used in bridges, construction industry and military industries.

Energy harvesting from the existing vibrations in nature and converting it into electrical energy causes the recovery of wasted energies and their optimal use. The obtained electrical energy can be used as a cheap, continuous and clean source to power low-consumption equipment such as sensors, actuators, controllers, medical equipment, etc.This article contains a rigid horizontal cylinder that has only vertical movement and is bounded by 4 springs.As a result of the wind hitting to the cylinder, a vortex induction force acts to the cylinder and causes vibration in the direction of perpendicular to the wind flow. A piezo-elastic energy harvesting system is placed inside this cylinder, which is connected to the horizontal cylinder through the fixed part of the beam.In fact, with the movement of the horizontal cylinder and through the vibration of the base, the force is transferred to the fixed part of the beam and causes the vibration of the piezo-elastic beam. The induced nonlinear force of the vortex due to the impact of the wind on the horizontal cylinder is calculated by applying the Vanderpol equation and its effect on the vibration of the equivalent system is investigated.Then, by using the piezoelectric element installed on the beam, the electric energy will be collected as the voltage. Here, the optimal wind speed and also the optimal electrical resistance are calculated in order to maximize the output electrical power. At the end, the effect of different parameters on the output power is investigated.

In this research, the dynamic response and vibration control of a sandwich piezoelectric cylindrical shell buried in an elastic medium under the effect of a moving ring load has been investigated. First, the dynamic equations of the shell are obtained based on Love's thin-walled shell theory, and then they are coupled with the governing equations of the surrounding elastic medium. Then, the resulting differential equations are solved using the Fourier transform, and after using Gauss's numerical integral for the inverse Fourier transform, the steady state dynamic response of the system is obtained. To reduce the vibrations caused by the moving load, a PID controller with optimized constants has been used. With extensive research done, the innovation presented in this research is the active reduction of the level of vibrations of a smart buried shell (pipe, tunnel) under the effect of a moving applied load. In a way, this innovation is at the same time being buried in the unlimited elastic environment and the piezoelectricity of the shell. The results show that the implemented controller is able to reduce the displacement range and stress in the system. Also, the operation of the piezoelectric active layer based on the appropriate controller reduces the sensitivity of the system to parameter changes.