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JournalISSN: 2321-3558

Journal of Vibration Engineering 

Springer Nature
About: Journal of Vibration Engineering is an academic journal. The journal publishes majorly in the area(s): Vibration & Nonlinear system. It has an ISSN identifier of 2321-3558. Over the lifetime, 886 publications have been published receiving 2538 citations.


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Journal ArticleDOI
TL;DR: Vibration analysis technique along with other condition monitoring techniques gives better results in the fault diagnostics and condition monitoring of rolling element bearing.
Abstract: 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.

85 citations

Journal ArticleDOI
TL;DR: The nonlinear passive isolation is effective for wide frequency bandwidth than the linear isolation system and the nonlinear energy harvesting system shows a great scope to harvest energy from wide ranges of excitations.
Abstract: Vibration present on various levels in many engineering fields and hence vibration mitigation has become a subject of intense study. The nonlinear vibration isolation devices are effective for broad frequency bandwidth and can provide better vibration isolation than linear devices. The need for nonlinearity in stiffness and damping characteristics has motivated researchers to apply the nonlinearity found in mechanisms or materials in the passive vibration control devices. This review discusses the applications of nonlinearity in the passive vibration control devices to provide an understanding of how the nonlinearity is applied and useful in the implemented system. Further, applications for nonlinearity can also be extended in the energy harvesting devices, Nonlinear energy sink, metamaterials for the purpose of vibration isolation and energy harvesting. The need for nonlinearity also encouraged research work through inspiration from the nature called bio-inspired devices. The bio-inspired devices mimic the nonlinearity of the biological system to suppress the vibrations. The nonlinear passive isolation is effective for wide frequency bandwidth than the linear isolation system. Further, the nonlinear systems also reduce transmissibility much efficiently than the linear system. The nonlinear energy harvesting system shows a great scope to harvest energy from wide ranges of excitations. The bio-inspired devices also are proven to be effective in vibration isolation. Additionally the design of the metamaterial with nonlinearity in the microstructure, proves to be promising in the vibration suppression applications. Based on the review, the nonlinearity introduced into the systems has greater benefits than the linear systems.

78 citations

Journal ArticleDOI
TL;DR: It is observed that the vibration-based techniques are reported to be effective for the identification of mechanical faults while motor current signature analysis is effective for electrical fault in an induction motor.
Abstract: An induction motor is at the heart of every rotating machine and hence it is a very vital component. Almost in every industry, around 90% of the machines apply an induction motor as a prime mover. It is a very important driving unit of the machine. Hence, it is necessary to monitor its condition to avoid any catastrophic failure and stoppage of production. The breakdown of the induction motor would not be affordable due to remarkable financial loss, unpredicted shutdown, and the associated repair cost. Vibration is a manifestation of induction motor due to the issues in alignment, balancing, and clearances. Bearing, the most vulnerable to failure due to continuous working under fatigue loading leads to defects. These defects cause changes in the vibration signature over time. The vibration monitoring techniques helps to effectively diagnose mechanical faults such as bearing defect and stator rotor rub. The purpose of this review paper is to summarize the major faults in induction motor, recent diagnostics methods augmented with advanced signal processing techniques, and real-life applications in electric vehicles. It also discusses possible research gaps and opportunities to contribute based on the review findings in the field of condition monitoring. This article presents a detailed review of recent trends in the research of condition monitoring and fault diagnosis of the induction motor. The emphasis is given on the major faults in the induction motor covering time-domain, frequency-domain, and time–frequency domain methods along with an application of artificial intelligence techniques for fault detection. This article presents a comprehensive review of literature which highlights the development and new propositions by researchers in the field of diagnostic techniques for the different faults of induction motor in the last decade. Researchers documented applications of the different conventional methods, advanced signal processing techniques, and soft computing techniques for fault identification of induction motor. This review is carried out for fault identification of induction motor used in machines in general and in particular for identifying the faults in an induction motor of an electric vehicle. A dedicated discussion on the review findings, research gaps, future trends in the field of condition monitoring of induction motor is presented. Condition monitoring of the induction motor in an electric vehicle is also discussed in this paper. It is observed that the vibration-based techniques are reported to be effective for the identification of mechanical faults while motor current signature analysis is effective for electrical fault in an induction motor. The review presented to analyze the suitability of various condition monitoring techniques for the induction motor fault identification in general and particularly its application in an electric vehicle. It is observed that the diagnosis of faults at the incipient level without using the signal processing technique is challenging. Fault diagnosis of induction motor has witnessed the changes from traditional diagnosis techniques to advanced techniques with a hybrid application of signal processing and artificial intelligence techniques. Still, there is a potential of improvement in reliability, efficiency, robustness, computational time, and real-time diagnostics of faults in IM.

51 citations

Journal ArticleDOI
TL;DR: The results show that the proposed system significantly improves both, the vibration attenuation ability and the ride quality of the vehicle.
Abstract: In this paper, Bouc–Wen type magnetorheological fluid damper has been used to monitor the ride quality of a prevailing rail vehicle in lateral vibrations. Modelling of the rail vehicle is done in such a manner that it has an entire 9 degrees of freedom by significant considerations of lateral, roll and yaw motions of the car body, rear, and the front chassis. 200 km/h is considered as train speed for tracks with two varying disturbances. A system consisting of multibody in VI-rail software is provided by a track input and ergo, wheel response it obtained. SIMULINK (software) is responsible for the representation of the motions of the wheel as mathematical models. Two different types of analysis are done firstly with conventional passive lateral damper and secondly with semi-active MR lateral damper in subordinate suspension. To diminish lateral vibrations, the disturbance refusal and non-stop state controller algorithms were executed to manage the damper force. Results acquired are in the form of acceleration and displacement of the center of mass of the body under consideration is done by comparing in terms of reduction indices of their vibrations. A significant improvement in the index is seen in which a semi-active lateral damper is mounted. The results show that the proposed system significantly improves both, the vibration attenuation ability and the ride quality of the vehicle.

50 citations

Journal ArticleDOI
TL;DR: In this paper, a semi-active method for vibration control of flexible structures using smart materials of electrorheological fluids, magnetorheological fluid and elastomers is presented.
Abstract: Vibration control is very significant issue in various engineering fields such as flexible structures, rotor systems, cable and bridge, and vehicle suspension. So far, three different recipes to suppress or control unwanted vibrations are used: passive, semi-active and active. As well known, the passive method has several limitations, such as the lack of real-time avoidance of the time-varying resonances. On the one hand, active vibration control method is very effective, but it is not attractive in terms of cost due to the use of several actuators and sensors. Therefore, recently semi-active vibration control method is popularly used in many practical environments. This article reviews vibration control of flexible structures using the semi-active method associated with smart materials of electrorheological fluids, magnetorheological fluids and magnetorheological elastomers. Modal characteristics of beam, shell and plate incorporating the core (or layer) of smart materials are deeply investigated and discussed in terms of field-dependent controllability. The field-dependent natural frequency and damping property of the sandwich beam type, plate type and shell type are experimentally identified. Subsequently, an appropriate control scheme based on the field-dependent modal properties is formulated to avoid the resonance behavior. In addition, several sandwich beams which are partially filled and fully filled with the magnetorheological fluid are investigated to understand the effectiveness of the modal property change. It has shown that both damping and stiffness properties of the sandwich structures can be effectively controlled by several ways: the change of the field intensity, the location of cores zones, the partial and full treatment and boundary conditions of the structures. In addition, it has identified that mode shapes of the sandwich plates featuring electrorheological core can be partially and fully controlled by applying the input field to an appropriate zone. Smart flexible structures associated with the field-responsive materials can be effectively used for vibration control due to its controllability of the stiffness and damping as well. However, to successfully implement in real environment, a more sophisticated analytical model considering the microscopic aspects of the particle motions needs to developed. Moreover, the field-dependent bucking problem and acoustic characteristics of smart structures subjected to external disturbances need to be explored.

43 citations

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Performance
Metrics
No. of papers from the Journal in previous years
YearPapers
2021198
202080
201960
201848
20171
20163