abdolreza ohadi

Investigating the sound radiated from faulty rolling element bearings (REBs) in rotor-bearing systems is as crucial as studying their vibration characteristics. This approach offers experts and researchers a more comprehensive understanding of faulty REB behavior, enhancing fault diagnosis capabilities. This study examines the impact of bearing faults, pedestal looseness, and shaft eccentricity on the vibro-acoustic characteristics of REBs. Additionally, it assesses the influence of fault severity and compound fault scenarios on these behaviors. A 6-degree-of-freedom (DOF) dynamic model is developed for an SKF 6205 bearing, including the shaft, inner ring, outer ring, and pedestal. The Hertzian theory is employed to model contact between the bearing balls and inner/outer rings. The governing equations are solved using the Runge-Kutta method to determine the surface velocity of the REB components, yielding a 4.56% error compared to experimental results, demonstrating good agreement. Based on the surface velocity, the sound pressure level (SPL) is calculated by modeling the inner and outer rings as cylindrical sound sources. The results reveal that auditory and visual observation can identify shaft eccentricity, while sound is a more sensitive indicator of bearing faults. Detecting incipient faults remains challenging, regardless of whether vibration or sound measurement tools, such as accelerometers or sound level meters, are employed. Furthermore, phase portraits indicate that pedestal looseness and bearing faults, unlike shaft eccentricity, result in chaotic and unpredictable motion, which may explain the sudden failures often observed in industrial REBs.

This research addresses the detection of camshaft axial clearance defects in internal combustion engines during end-of-line hot testing using acoustic signal processing. The study's importance lies in reducing manufacturing costs and enhancing customer satisfaction through improved product quality. This defect is prevalent in the production line and challenging to identify using conventional methods.The research proposes an intelligent solution for defect detection by combining time-frequency domain signal processing techniques with artificial neural networks. The axial clearance defect was simulated at various severity levels, and acoustic signals were recorded using a handy sound recording device at three different engine speeds (1300, 1700, and 2500 RPM) under no-load conditions. The engines undergo a seven-minute test at these different speeds to ensure proper functionality. The choice of a handy recorder device was based on the manufacturer's request for a portable and cost-effective solution.It's noteworthy that the recorded audio data contains noise due to production line conditions, adding complexity to the fault diagnosis process. For signal processing and feature extraction, two methods were employed: Continuous Wavelet Transform (CWT) and Mel Spectrogram.The results demonstrate that the Mel Spectrogram is more effective for feature extraction compared to the Continuous Wavelet Transform. At operating speeds of 1700 RPM and 2500 RPM, all defect levels are detected with an average accuracy of 99% by using Convolutional Neural Network.This study contributes to the field of non-invasive fault detection in automotive manufacturing, offering a reliable and cost-effective method for identifying camshaft axial clearance defects. The high accuracy achieved at specific operating speeds suggests that this approach could be implemented in real-world production environments, potentially leading to significant improvements in quality control processes and overall product reliability.The success of this method highlights the potential of acoustic signal processing and machine learning techniques in solving complex industrial quality control challenges.

Despite the extensive progress in the field of biomechanics of human gait, a suitable gait model with the ability to simulate the control system of the human brain has not yet been presented, especially in 3D mode. The importance of the issue increases when the simulation of human walking is one of the main requirements of designers of biomechanical equipment such as artificial organs, wearable robots and humanoid robots. Regarding the constraints and complexities of previous studies, in this research, a forward dynamic 3D model of gait based on sliding mode controller (SMC) is presented, which simulates the walking behavior of healthy individual on the ground in different movement phases. One of the strengths of this research is the comprehensive and analytical review of 3D rotation consequences of the joints coordinate systems, which is done with 11 DOF inverse dynamic model. Based on the obtained results, the SMC controller is well able to produce stable 3D human gait. Also, in 3D gait analysis, the Cardan rotation sequence is not suitable and YXZ order should be used. This outcome is a very useful result for 3D motion generation for human like walking pattern. The results of this study can be used in the design of humanoid robots, active and passive prostheses. Also, the presented model can simulate the walking of an amputee with a prosthesis and the role of the controller in the path, which is very important and beneficial in terms of rehabilitation.

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).

Quadrotors provide exclusive performances like vertical landing and taking off, load carrying capacity, and possibility of remote control. A pertinent deficiency of them however concerns their underactuated configuration, which is one of the inherent characteristics of these robots. A dependency between different movements of quadrotor is unavoidable due to this characteristic. To eliminate the dependencies between linear and rotational motions and so increase the number of controllable degrees of freedom, a novel configuration has been presented for the fully-actuated quadrotor. The rotors have the ability to rotate around two perpendicular directions and two degrees of freedom have been added to the system. The motion dependencies between linear and angular degrees are omitted. To investigate the capability of the fully-actuated quadrotor, the novel configuration is introduced and the capabilities of this configuration in eliminating movement dependencies are discussed. To this end, after extracting the motion equations governing the fully-actuated quadrotor using Newton-Euler method and applying a proportional-derivative controller to the model, the performance of this configuration in eliminating the motion dependencies is compared against a conventional underactuated type. It is shown that this configuration is capable of eliminating motion dependencies to a great extent within various simulation results. Finally, by designing a back-stepping controller and applying different trajectories to the proposed fully-actuated quadrotor, its motion capabilities and limitations are thoroughly investigated.

The complexity of tire/road noise generation and amplification mechanisms has made it challenging for tire builders to reduce emitted sound. Statistical methods help to model complex problems. This paper predicts tire noise level by a superior regression method in machine learning, relevance vector machine, with a total noise prediction error of 0.62 dB(A). The tire’s noise sensitivity to its parameters is analyzed by applying a small central composite design to the developed model. The effect of grooves’ shapes on tire noise is preserved in the results, unlike the previous publications. For a case study, grooves’ depth has been recognized as critical in controlling tire noise. Based on the variance analysis results, the interaction of this parameter with the number, length, and width of transverse grooves has also been identified as significant. According to the parametric study’s striking tips, two sets of tread pattern specifications are proposed for noise reduction, utilizing the response surface method. They reduce the noise level by 1.72 and 1.54 dB(A) for a tire with a measured noise of 75.88 dB(A)

In recent years, in most countries of the world, the provision of a calming environment without disturbing noise has become a need, which has subsequently led to significant growth in noise control techniques. It is now well documented that prolonged over-exposure to the excessive levels of environmental noise not only induces disabling hearing impairment but also contributes to numerous adverse health effects such as stress, irritability, hypertension, cardiovascular diseases, annoyance, and sleep disturbance. Working in noisy environments has also been reported to be linked with increased workplace accidents, aggression and anti-social behaviours. Based on the World Health Organization (WHO), occupational noise accounts for 16% of the disabling hearing loss in adults (more than four million DALYs), with estimates of disease burden ranging from 7% in developed countries to 21% in underdeveloped and developing nations.
There are several methods to reduce the noise pollution and control the sound of the working environment; one of the methods of controlling sound propagation path is the use of insulation and sound absorption. Sound control improvements with using sound absorption materials have provided a suitable opportunity to study noise reduction and acoustic attenuation by using a variety of porous materials. Increasing concerns about the adverse effects of the use of synthetic sound absorbing materials on the health of individuals has provided a favorable ground for the development of research on the use of natural fibers as insulators and absorbents. During the last two decades, there has been considerable interest in the use of lignocellulosic fibres for various purposes such as sustainable acoustic absorbers.  Bio-based composites of acoustic absorbers are mainly biodegradable and non-toxic and have low weight, low density and low cost and can be used as alternatives to the absorbers made of synthetic fibres.
Every year, in Iran, significant amounts of agricultural waste containing lignocellulosic fibres are burnt or disposed of improperly due to the lack of a proper recycling system and reusing mechanisms. However, a large proportion of such waste can be used for various uses. Iran as the second largest producer of dates in the world, and having large date palm plantations, faces the scourge of harvesting and pruning palm trees each year, which are largely suitable for use.
Therefore, the purpose of the present study was to investigate the acoustic behaviour of composite samples made of date palm natural fibres by predicting their sound absorption coefficients with the related experimental models and comparing the results with the data obtained from the experimental tests.

In this study, the natural date palm waste fibers were procured from Tabas city in southern Khorasan province in Iran. Having transferred to the laboratory, the raw DPFs were rinsed with distilled water before being placed inside an oven at 70 °C for 24 hours to dry and get a fixed weight. The DPFs were then cut into smaller pieces by a pair of scissors and crushed and pressed through a 2 mm mesh sieve to make their size fairly homogenous. In order to bind the fibers together and form a composite, polyvinyl alcohol (Sigma-Aldrich) was utilized. PVA is a polymeric chemical binder with high solubility in water and is known to be a biodegradable material reportedly used as natural fiber binder in previous studies.
In order to prepare 5% PVA concentration, 5 g of the substance was first weighed by a scale and later dissolved in 100 ml of distilled water. The solution was then stirred with a magnet at 80 °C for 3 hours. Having prepared the solution, the fibers were soaked with it to bind. The fibers were then shaped by an aluminum mold (by compression molding) to be fitted inside the impedance tube (internal diameter of 100 mm) and form samples with thicknesses of 20, 30 and 40 mm with a constant density of 200 kg/ m3. After the molding process, the samples were left at room temperature for 12 hours to dry completely before being transferred to the laboratory for absorption coefficient measurement. SEM images showed that outer diameter of the DPFs ranged from 200 to 720 μm and the mean diameter, the density and porosity of them were 420 μm, 930 kg/m3 and >80% respectively. The measurement of normal incidence absorption coefficients of the samples with a constant density and three different thicknesses a different air gaps was performed by an impedance tube and based on ISO 10534-2. Afterwards, by creating the appropriate codes in MATLAB software, using the differential equation algorithm, the predicted sound absorption coefficients for the Delany-Bazley, Micky, and Johnson-Champoux-Allard models were calculated. In fact, such algorithm searches for the three parameters until the best fit (minimized difference) is observed between the experimental and theoretical absorption curves. Therefore, the experimental sound absorption curve for the samples of the corresponding date palm fibers was first determined by the impedance tube system. We followed the same method proposed by Atalla and Panneton.

The results from the laboratory data for the three thicknesses of 20, 30 and 40 mm of the sample absorbers of DPF and the impact of the air gaps on their sound absorption coefficients are presented. Using the mathematical model, the sound absorption coefficient in the frequency range of 125-6300 Hz was next coded by MATLAB software. As shown in this paper, the predicted values of the physical parameters of the DPF were measured using differential equation algorithm in the MATLAB software through the available laboratory data such as the thickness, density, airflow resistivity and absorption coefficient. Later, the prediction error rate determined by the JCA model - shown on the right axes is compared to the data obtained from the experiments. The results showed that the sound absorption coefficients of the samples fabricated from date palm fibres, significantly increased with increasing the frequency. Moreover, the increase in the thickness of the samples with a constant density has a major role in attenuating the sound waves, especially in lower frequencies (less than 1000 Hz). Comparison of experimental data and models output showed that by increasing the thickness, the predicted values for the acoustic absorption coefficient of the samples approach the values obtained from the experimental tests. As can be seen, the JCA model has a fair accuracy in predicting the absorption coefficient in different thicknesses compared to the Delany-Bazley and Micki models.
Thus, this model at 20, 30- and 40-mm thickness and lower frequency range (63-1600 Hz) showed different prediction accuracies of 23%, 6% and 11% respectively, while at higher frequency range (1600-6300 Hz) came up with 9%, 6% and 4% prediction accuracies. Thus, such agreement is considered as significant in the higher frequency range. These findings also indicate that the outputs of the JCA model, rather than two other models, are closer to the data obtained from the experimental tests for setting the sound absorption coefficients. It is therefore concluded that the JCA model (compared to the Delaney-Basile and Mickey models) has included more dominant parameters that might impact the physical properties of the samples such as thickness, mass density, sample resistance against airflow, tortuosity, viscous and thermal characteristic length. Introduction of air gap behind the DPF samples in the impedance tube transfers the maximum values of sound absorption coefficient from the upper to the lower frequency range. The results indicate that, as the sample distance from the rigid surface of the backing (up to 30 mm) increases, the sound absorption coefficient at frequencies lower than 1000 Hz will rise as well. As a result, used in this study absorbing materials with an air cavity behind them seems to play a significant role in lower production cost, and thinner layers of absorbing materials yield better absorption coefficients. The reason for this behavior is probably due to the increased impedance of absorbing material. In this case, the acoustic resonance transferred towards lower frequencies and thus improved the values of absorption performance in that range. As a result, it seems that the use of absorbing material, while having a layer of air behind them, can reduce the cost and material consumption. Thus, thinner samples made of coir fibers would provide superior values of sound absorption coefficients.

Date palm fibres have a great potential for attenuating the energy of sound waves. Elevated levels of sound absorption can be attributed to a longer dissipative process of viscous and thermal conduction between air and the absorber.  Therefore, increasing the thickness of the sample will contribute to higher amounts of sound absorption coefficient.
On the other hand, natural fibers are still not as popular as synthetic fibers due to the properties such as low adhesion, high fiber diameter, low resistance to moisture and vulnerability to fungi. Therefore, it is obvious that these factors can affect the absorption coefficient of sound and the quality and durability of acoustic panels made of such natural fibers. In order to eliminate these defects, nanotechnology can be employed to achieve superior properties and better conditions by utilizing the best of these natural materials. Evidently this is the issue that should be taken into account in developing sound absorbers which are originated from the natural fibers.

The fixtures play a significant role in harnessing the metal sheets in the assembly stage. The high flexibility of the metal sheets and the initial deviation in the pressed sheets cause deviation in the final product. Using the optimal layout of the clamping points in the fixture can reduce the deviation effectively and raising the final product quality. On the other hand, the cost of construction is intensively influence by the number of clamps, rising the number of clamps causes the cost of construction to increase and reducing it cause the deviation in the final product to increase. Therefore, the number of clamps should be considered in the optimal design of the fixture. It is challenging to achieve optimal design for fixture due to the difficulty in predicting sheet behavior and computational constraints. In this paper the relationship between the initial deviation of sheet and the deviation of final product is investigated and a method is proposed by using ant colony algorithm and finite element method for optimizing the position of the clamping points to reducing the deviation of the product after assembly with considering the minimizing the number of clamping points. Finally the proposed method is applied to a simple square sheet with initial deviation and based on the cost function, the number of clamping points and their position are optimized. The results show that reducing the amount of sheet deviation in the fixture causes reduce the deviation of final product.

It is possible to improve vehicle vibration by tuning the parameters of engine mounting system. By optimization of mount characteristics or finding the optimal position of mounts, vibration of the engine and transmitted force from the engine to the chassis can be reduced. This paper examines the optimization of 6-degree-of-freedom engine mounting system based on torque roll axis (TRA) mode decoupling, so that TRA direction coincides with one of the natural modes of vibration. This is achieved by determination of optimal location and stiffness of mounts. In order to find feasible results, physical constraints are taken into account in optimization process. A detailed procedure of optimization problem is explained. Finally, by comparing the frequency and time responses of the optimal design with the original configuration, it is concluded that TRA decoupling is a proper objective function in engine mounting optimization and can greatly improve the vibration behavior of the engine. Achieving decoupled system, the optimal configuration has a better chance of placing dominant natural frequency below the operation range. Also, the forces transmitted through the mounts are reduced noticeably in the optimal design.

Squeeze Film Dampers (SFD) are commonly used for passive vibration control of rotor-bearing systems. The Magnetorheological (MR) and Electrorheological (ER) fluids in SFDs give a varying damping characteristic to the bearing that can provide active control schemes for the rotor-bearing system. A common way to model an MR bearing is implementing the Bingham plastic model. Adding this model to the finite element (F.E.) model of the rotor enables analyzing the rotor bearing behavior. In this work, considering uncertainties, three types of controllers are designed for a rotor-bearing system and the efficiency of using these controllers in attenuating the vibration amplitude of the system is studied. As a result, employing these controllers reveals a remarkable improvement in reducing the vibration amplitude of the shaft midpoint near the critical velocity.

In this paper the influence of non-acoustic properties on the sound absorption coefficient of polyurethane foams as a porous medium is investigated. Biot’s equations with transfer matrix method, as the solution approach are employed to evaluate the sound absorption coefficient of selected polyurethane foams. The major issue is the dependency of non-acoustic properties on each other which makes difficulties to examine the effect of parameters individually. Some facts from the results of previous works are used in order to overcome this prominent obstacle. The results show that increasing the porosity doesn’t have a great influence on the sound absorption coefficient and only for highly porous foams, raising porosity decreases the sound absorption performance. The increase of air flow resistivity up to an optimized value, intensifies the absorption capability. Furthermore, for partially reticulated (partially open cell) foams, the increase of tortuosity improves the sound absorption efficiency at lower frequencies.

The aim of this paper is robust identification of smart foam, as an electroacoustic transducer, considering unmodeled dynamics due to nonlinearities in behaviour at low frequencies and measurement noise at high frequencies as existent uncertainties. Set membership estimation combined with model error modelling technique is used where the approach is based on worst case scenario with unknown but bounded uncertainties. The outcome is a robust identified model which consists of a nominal model with its uncertainty bounds that fits exactly the H_∞ robust control scheme which has been utilized in active noise control in recent years. While the nominal model has the desired physical characteristics as cut-off frequency and the anticipated slope and flatness before and after this frequency, respectively, it is maintained in the acceptably tight uncertainty upper and lower limits, thus validating the identification procedure. Looseness and tightness of uncertainty strip has also been discussed regarding nonlinearities and measurement noise in low and high frequency regions. Meanwhile the identified nominal model can also be utilized in non-robust noise control methods due to its lower order, reflecting the advantage of the applied identification approach.

Sound power is considered as anexcellent measure for evaluating the efficiency of noise controls as well as for comparing noise sources in workrooms. This parameter can bedetermined bysound pressure or intensity based methods in real conditions of workrooms. This paper aims empiricallyto compare these in situ methods in relation to a typical industrial machine located in workroom interms ofaccuracy, applicability. Determination of sound powerof a typical model of noisy embroidery machine located in enclosed workroom wasperformedin theinterested frequency range of 125Hz to4000 Hz. Field measurementof sound power wasconducted using the BSWA sound analyzer according toISO 9614 and ISO 3746, respectively. The resultsshowed SWL spectrum of the source was relatively high with flat noise spectrum.Operation speed was one of the most important features which could influencethe noise of embroidery machine. In regard to uncertainty values, the sound power spectra, obtained using the two methods,showed acceptable agreement from the viewpoint of applicability. Thehigher value for pressure methods can be due to fluctuations in background noise and methodlimitations. Direct measurement ofreverberation time compared with approximate method could improve the accuracyof the pressure method. Hence, pressure method can be employed by occupationalhealth experts as analternative to intensity method. Due to its direct and more accurate measurements, intensity method is considered to be amore preferred technique in order to describe any noise sourcesand to evaluatenoise controls at sources.

Passive walkers are robots، which perform a walking like، stable limit cycle on small slopes without any external control. This concept was published on 90’s by McGeer and there are lots of related researches going on in the past few years. Keeping in mind the novelty of the concept، investigating the effects of structural parameters on walking performance and finding their optimums، simulating the biped and establishing a trend to its optimal design and build، and finally doing experimental researches، would be of a great concern. In this research، a deployed model of biped that can be built has been considered، and then its walking performance sensitivity such as efficiency، stability and robustness on uneven trains due to variation of structural parameters and their optimum limits have been investigated. It was shown that the foot arc radius and center of mass height have the most important effect on walking performance. After comparing the results with previous researches and doing simulations in MSC. ADAMS software، an optimum design trend has been suggested. At the end based on experimental results، it was shown beside optimization of structural parameters، considering the impact condition as well would be very important to achieve optimal walking.