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        Calculation of time dependent mesh stiffness of helical planetary gear system using analytical approach

        Mohsen Rezaei,Mehrdad Poursina,Shahram Hadian Jazi,Farhad Haji Aboutalebi 대한기계학회 2018 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.32 No.8

        Time-dependent mesh stiffness is a most important reason of vibration and dynamic excitation in gear sets. In this research, analytical formulas of the helical gear set and the planetary gear system are combined to calculate the time-dependent mesh stiffness of the helical planetary gear system. For this purpose, at the first step, the analytical equations are derived for the spur gear pair. Then by dividing a helical tooth into the several independent thin spur tooth slices, the helical gear pair mesh stiffness is extracted. Finally, these equations are extended to the helical planetary gear system. The suggested analytical results and those which obtained by the finite element method (FEM) are compared and are in good agreement when the helix angle is less than 15 degrees. Also, the helical planetary gear system mesh stiffness in different cases such as fixed carrier, fixed sun gear and fixed ring gears is calculated. These results show that the value of mesh frequency ratio in each case scales the mesh stiffness shapes in the rotation angle direction. In other words, mesh frequency ratio parameter determines the number of meshing period in each rotation of planets.

      • KCI등재

        Multi crack detection in helical gear teeth using transmission error ratio

        Mohsen Rezaei,Mehrdad Poursina,Shahram Hadian Jazi,Farhad Haji Aboutalebi 대한기계학회 2019 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.33 No.3

        Gear systems are used to transmit power in the industry when accuracy and synchrony are needed and helical gear systems are used in more accurate and high-speed industries. It is important to ensure that these systems work faultlessly, therefore the detection of the crack location and situation is very efficient in the gear systems. In this research, a new approach is proposed to detect the multi crack location and length in the helical gear teeth. To this end, after giving an explanation of helical gear mesh stiffness and demonstrating the helical gear pair dynamic modeling, the transmission error ratio method is used to detect the cracks locations and lengths. Then, according to solved examples, when the cracks locations are far enough that their effects on the transmission error are completely separated, the cracked teeth and the lengths of cracks can be detected exactly, and when the cracks are in adjacent teeth, according to the cracks lengths and depths and their effects overlap, the number of cracks and their lengths can be detected exactly, approximately or absolutely undetectable.

      • KCI등재

        Estimation of minimum horizontal stress, geomechanical modeling and hybrid neural network based on conventional well logging data – a case study

        Majid Jamshidian,Mostafa Mansouri Zadeh,Mohsen Hadian,Sahand Nekoeian,Morteza Mansouri Zadeh 한국자원공학회 2017 Geosystem engineering Vol.20 No.2

        The minimum horizontal stress (Shmin) is one of the three principal stresses and is required for evaluation of the hydraulic fracturing, sand production, and well stability. Shmin is obtained using direct methods such as the leak-off and mini-frac tests or using some equations like the poroelastic equation. These equations require some information including the elastic parameters, shear sonic logs, core data and the pore pressure. In this study, a geomechanical model is constructed to obtain the minimum horizontal stress; then, an artificial neural network (ANN) with multilayer perceptron and feedforward backpropagation algorithm based on the conventional well logging data is applied to predict the Shmin. Cuckoo optimization algorithm (COA), imperialist competitive algorithm, particle swarm optimization and genetic algorithm are also utilized to optimize the ANN. The proposed methodology is applied in two wells in the reservoir rock located at the southwest of Iran, one for training, and the other one for testing purposes. It is found that the performance of the COA–ANN is better than the other methods. Finally, Shmin values can be estimated by the conventional well logging data without having the required parameters of the poroelastic equation.

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