In this study, the effectiveness of these measures in reduction of vehicles Speed has been considered, considering the extensive use of Speed humps and humps as physical traffic calming measures in Iran, especially in the northern provinces (due to high accesses, interference of social roles and displacement of road, and the significant difference between Speed of vehicles and Speed limit). This study was carried out to determine the relationship between geometric characteristics of humps and vehicles Speed in 90 different areas of roads in eastern part of Mazandaran province. Since the studied sample consisted of all types of humps, including arches and beds and they performed in different functional classes of roads, they were categorized for better examination and Separately, each geometric feature was identified. and the Speed of vehicles were determined individually around them. The Speed of the vehicle was recorded at a few points before, on the humps and then it was recorded using a Speedometer camera, and their dimensions were surveyed accurately by using the Total Station camera. Finally, data was evaluated using linear regression model in SPSS software and has been presented the main factors affecting vehicle Speed reduction and models related to Speed reduction. Considering the high number of selected humps in the study, the results of this research showed that it is possible to use these models to design and implement humps for passage Speed and different specific Speeds; in addition, these models could evaluate the effectiveness of the humps in Speed reduction, and determine the Speed profile at different distances from the humps in a high level of confidence.

This paper describes a simple way to control the Brush Less DC Motor (BLDCM) for electrical applications. To control this machine it is generally required to measure the Speed and position of rotor by using the sensor because the inverter phases, acting at any time, must be commutated depending on the rotor position. The position sensors make the motor system more complicated and mechanically unreliable. A method for the estimation of the Speed and rotor position of a BLDCM is presented in this work. Fuzzy based Back EMF observer is employed to estimate the Speed by using measurements of the stator line voltage and line current. Most existing sensorless methods of the BLDC motor have low performance at transients or low Speed range and occasionally require an additional circuit. To overcome this problem, the estimation of a back-EMF is carried out by fuzzy logic techniques to improve the performance of the system. This method proposes back-EMF observer based on fuzzy function approximation and the system state equation of the BLDC motor. The fuzzy logic technique is used to estimate the Speed of the BLDC motor under variable and fixed condition of the back-EMF. Finally, the Speed is controlled by using Proportional-Integral (PI) Controller with the help of fuzzy based estimation of the Speed and rotor position. Here, fuzzy based estimation of Speed and rotor position which is also verified with the sensor, feeds input to the PI controller which does really well for good performance.

Recently, performance improvement and Speed control of Single-Phase Induction Motors (SPIMs) have been paid attention. These aims is required the machine Speed. In this paper, a method is proposed to estimate the SPIMs Speed, and then, its application in torque optimization of the machine is investigated. For this purpose, the motor Speed is obtained in terms of the motor parameters and stator flux linkage components by use of the SPIMs equations in stationary reference frame. By obtaining the flux linkage from motor windings voltages and currents, the motor Speed is estimated desirably. Then the estimated Speed is used to increase the average torque, to decrease the pulsation torque and to optimize the motor torque. After that, the simulation results in condition of using the real Speed are compared with the estimated Speed one. The low simulation error proves the validity of the proposed method.

One of the major issues related to traffic monitoring systems is analyzing the behavior of vehicles and identifying their characteristics. In this paper, an automated algorithm is proposed for calibration of the road cameras. This calibration is used to estimate the Speed and dimensions of the passing vehicles. In this method, a motion plane is obtained in the initial frames according to the direction of moving vehicles. After modeling the background, removing shadows, and identifying the exact boundaries of passing vehicles, a number of common vehicles are recognized by the Bag of Words method. Given the actual metric dimensions of these vehicles and the equivalent dimensions on the motion plane, the metric coefficients are calculated and the calibration process is completed. Each passing vehicle is projected on the motion plane, and Speed and dimensions are calculated by tracking it along the road. To test the accuracy of the proposed method, we constructed a ground-truth video dataset, by simultaneous capturing the road vehicles using RGB and Speed cameras. Furthermore, to identify common vehicles, a dataset of vehicle images was collected. The proposed method evaluated on our dataset and the mean error of 1. 15 km/h is achieved. Accordingly, it outperforms previous methods.

Permanent Magnet Synchronous Machines (PMSM) are increasingly used because of their advantages over other machines, which include compactness, high efficiency, and well developed drives.. The substitution of the position sensors by advanced algorithms embedded in the controls hardware and software has been investigated for the last couple of decades. This Paper presents the modeling, analysis, design and experimental validation of a robust sensor less control method for PMSM based on Extended Kalman Filter. The position/Speed sensor less control scheme along with the power electronic circuitry is modeled. The performance of the proposed control is assessed and verified for different types of dynamic and static torque loads.

In this article, an attempt has been made to estimate the amount of sound transmission loss in a flat oval channel by applying the approach of statistical energy analysis. Correct estimation of sound transmission loss in an air conditioning channel is of great importance due to the harmful effects of noise pollution in the environment on human health. Simulation with the statistical energy analysis method is a powerful approach to estimate sound and vibration in problems in which we deal with complex and multi-part systems; is considered. In this method, first, a system is divided into several subsystems, and then by writing a matrix equation that includes the energy exchanges between subsystems and energy loss coefficients; It is investigated from the perspective of vibration and sound estimation.On average, the model presented in this research is able to estimate the sound transmission loss in different dimensions of the air conditioning channels according to the experimental results in the accuracy range of ± 2.5 dB. Considering that it seems that the results obtained from modeling with this method are in good agreement with the experimental data; The results of this research can be used as an efficient approach to estimate noise in oval shaped channels stretched in different lengths.

Single-phase motors are among the most widely-used motors in low-power applications. These motors are omnipresent in residential applications and make up a majority of this sector. Previously these motors were specifically employed in constant velocities. Over time the need for Speed control in these motors has brought this problem into focus of many research investigations. Sensorless control of single-phase motors is particularly appealing due to mechanical and economic considerations. In the present paper, one attempts to control motor Speed by influencing rotor flux orientation through a vector control method and propose a new method of Speed estimation based on extended Kalman filter algorithm. In order to estimate single-phase induction motor Speed together with on-line rotor resistance estimation, the measurement noises have been accounted in EKF algorithm. The proposed method is validated with a simulation that includes rotor resistance changes and measurement noise.