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(a) System identification toolbox window (b) Transfer function estimation in system identification toolbox
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Actuators based on smart materials such as piezoelectric actuators (PEAs) are widely used in many applications to transform electrical signal to mechanical signal and vice versa. However, the major drawbacks for these smart actuators are hysteresis nonlinear, creep and residual vibration. In this paper, PEAs are used for active vibration applicatio...
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Cereal-legume intercropping has gained increased interest in Europe. Nevertheless, performance and especially the percentage of each species at harvest are often considered highly variable. Nitrogen (N) fertilisation can be a relevant driving factor affecting the percentage of each species at harvest. Soil N availability influences competition for...
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... The PSD represents the statistical average of the power spectral characteristic of a signal. PSD can be used to analyze the strength and weakness of a signal in the frequency domain in terms of energy [19]- [22]. Therefore, to analyze the vibration signal at the measuring points, in this paper, PSD analysis is used. ...
... Figure 7 is PSD analysis of vibrations for 3 axes, it shows that the power of vibration energies is concentrated highly at several frequencies. The vibration energy of z-axis is high at frequencies as 2.955 , 23.99 , 40.55 , 59. 19 and 83.96 respectively with the power spectral density respectively 0.03517 2 / 3 , 0.02319 2 / 3 , 0.02319 2 / 3 , 0.0006748 2 / 3 , and 0.00115 2 / 3 . There are 03 frequencies concentrating highly vibration energy in the axis as 3.993 , 11.98 , and 24.87 , the power spectral density of these frequencies is 0.005406 2 / 3 , 0.004013 2 / 3 , and 0.003591 2 / 3 . ...
span lang="EN-US">This paper presents a design of soft-gauge using the low-cost triple-axis accelerometer MMA7361L and LabVIEW software for the purpose of elevator vibration analysis with accuracy according to national standards. The 3-dimensional vibration signals measured and collected respectively by MMA7361L and NI USB6009 are fed into a soft-gauge programmed on LabVIEW to filter, then the fast Fourier transform (FFT) is applied to determine the power spectral density (PSD) and spectrogram of vibrations of filtered vibration signals. The soft-gauge also allows real-time 3-dimensional vibration data to be recorded, this data is used for analyzing later by another professional data software. Practical test results applied for the elevator of the DONGA Plaza building show quite good vibration analysis. Class 1.5 accuracy of the soft-gauge can be obtained by experimental test. This is a fairly cost-effective and inexpensive application that can be made in conditions with limited funds that cannot afford expensive accelerometers in the training of vibration measurement and analysis in high schools and vocational schools in developing countries, like Vietnam.</span
... Consequently, the control problems involve finding suitable mathematical models that describe the dynamic behaviour of the physical mass spring dampers (MSD) model to permit suitable controller design and allow corresponding control strategies to realize the expected system response and performance. Mass-spring-damper systems (MSD) are widely used in robot manipulator control [1], [2],vehicle suspension systems for shock absorption in automobiles [3]- [7], Mechatronic application especially in piezoelectric for vibration energy harvester [8]- [10] and motion control application [11]- [12]. Recently, MSD systems are in increasing demand for hybrid vehicle suspension to increase passenger ride comfort and vehicle stability over cracks and uneven pavement. ...
... A coupled mass spring damper systems adapted from[8] ...
This paper presents the use of Simelectronics Program for modeling and control of a two degrees-of freedom coupled mass-spring-damper mechanical system.The aims of this paper are to establish a mathematical model that represents the dynamic behaviour of a coupled mass-spring damper system and effectively control the mass position using both Simulink and Simelectronics.The mathematical model is derived based on the augmented Lagrange equation and to simulate the dynamic accurately a PD controller is implemented to compensate for the oscillation sustained by the system as a result of the complex conjugate pair poles near to the imaginary axis.The input force has been subjected to an obstacle to mimic actual challenges and to validate the mathematical model a Simulink and Simelectronics models were developed, consequently, the results of the models were compared. According to the result analysis, the controller tracked the position errors and stabilized the positions to zero within a settling time of 6.5sec and significantly reduced the overshoot by 99.5% and 99. 7% in Simulink and Simelectronics respectively. Furthermore, it is found that Simelectronics model proved to be capable having advantages of simplicity, less time-intense and requires no mathematical model over the Simulink approach. © 2018 Institute of Advanced Engineering and Science. All rights reserved.
In automation and mechatronics applications, mass spring damper system (MSDS) plays a significant role in ensuring model serviceability and safety. The system's dynamic of this mechanical system is quite challenging to control. In this paper, the system is a single degree of freedom (SDOF) spring mass system. The issue of performance evaluation of three controllers, linear proportional integral derivate (LPID), nonlinear PID (NPID), and fuzzy logic controller (FLC), is presented. FLC demands that experience be built on information based on a rule. It has two inputs, one of which is the displacement and the other is the velocity, and force is calculated for forced damped vibration control for a single degree of freedom system. The method used for defuzzification is the center of gravity (COG). However, effective control of a system depends largely on the accuracy of the mathematical model that predicts its dynamics behavior. The mathematical model for the MSDS is based on a set of nonlinear second-order ordinary differential equations to simulate the dynamic accurately. The proposed control schemes are implemented with the aid of MATLAB and SIMULINK to investigate the system performance. The sequence of the three controllers in terms of performance is as follows: the first of them is FLC and then in some dominant cases this is NPID by comparison with the LPID and one without any controller cases. Also, FLC displays more effectiveness and efficiency than the system without this controller after a comparative of system analysis performance evaluation.
