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Effect of payload magnitude on time histories of torques acting on the high-speed links. (a) The torque of the shaft connecting components J3 and J4 when braking starts at ne; (b) The torque of the shaft connecting components J4 and J5 when braking starts at ne; (c) The torque of the shaft connecting components J5 and J6 when braking starts at ne; (d) The torque of the shaft connecting components J3 and J4 when braking starts at −ne; (e) The torque of the shaft connecting components J4 and J5 when braking starts at −ne; (f) The torque of the shaft connecting components J5 and J6 when braking starts at −ne.
Source publication
Mechanical brakes are essential for electric cranes when emergency braking occurs. This paper presents, for the first-time, a dynamic response analysis of emergency braking events of electrical cranes that has modelled crane components as flexible and rigid bodies. Based on the Hamilton principle, a nonlinear and non-smooth dynamic model is derived...
Contexts in source publication
Context 1
... shown in Figure 9, the torque peaks and maximum torque range occur when the crane is under the rated load or in no-load condition; in the third phase of the braking process, the amplitudes of the high frequency components of TS3 increase obviously when the crane is in no-load condition. This result, namely the maximum braking time of the lifting mechanism and the maximum braking distance of a payload are determined by the process of lowering a rated payload at full speed, is consistent with rigid dynamic analysis. ...
Context 2
... shown in Figure 9, the torque peaks and maximum torque range occur when the crane is under the rated load or in no-load condition; in the third phase of the braking process, the amplitudes of the high frequency components of T S3 increase obviously when the crane is in no-load condition. This result, namely the maximum braking time of the lifting mechanism and the maximum braking distance of a payload are determined by the process of lowering a rated payload at full speed, is consistent with rigid dynamic analysis. ...
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Citations
... In the literature of the subject, one can mainly find works based on analytical models [3][4][5][6][7][8][9]. However, in the case of designing new devices, the use of CAD/CAE software to conduct numerical simulations is indispensable, especially during the strength analysis [10,11]. ...
Tracking the trajectory of the load carried by the rotary crane is an important problem that allows reducing the possibility of its damage by hitting an obstacle in its working area. On the basis of the trajectory, it is also possible to determine an appropriate control system that would allow for the safe transport of the load. This work concerns research on the load motion carried by a rotary crane. For this purpose, the laboratory crane model was designed in Solidworks software, and numerical simulations were made using the Motion module. The developed laboratory model is a scaled equivalent of the real Liebherr LTM 1020 object. The crane control included two movements: changing the inclination angle of the crane’s boom and rotation of the jib with the platform. On the basis of the developed model, a test stand was built, which allowed for the verification of numerical results. Event visualization and trajectory tracking were made using a dynamic vision sensor (DVS) and the Tracker program. Based on the obtained experimental results, the developed numerical model was verified. The proposed trajectory tracking method can be used to develop a control system to prevent collisions during the crane’s duty cycle.
Increasing the productivity of lifting machines and their reliability is possible by reducing the dynamic loads that occur at the lifting mechanism starting and braking. Carried out is the analysis of methods to reduce the lifting machines’ hoisting mechanism dynamic loads during the acceleration period when load lifting. The method chosen for our study is reducing the mass inertia moments of parts located on the hoisting mechanism’s slow-speed shafts. The study aimed to reduce the hoisting mechanism dynamic loads at cargo lifting by optimizing the gear drive mechanism design scheme. One of the promising methods to reduce dynamic loads in machine drives consists of the multithreading principle use. A new design scheme for the gearbox has been developed. This structure represents a multi-threaded two-stage gearbox, where each stage consists of a central gear, intermediate wheels, which axes are fixed in the housing, and a gear wheel with internal gearing. It has been established that using intermediate wheels of different diameters can obtain different gear ratios of the gearbox. It is determined that the minimum gear ratio for a two-stage multithreaded gearbox is 9. With such a gear ratio of the gearbox, the dynamic loads that occur during the lifting mechanism drive start-up are minimal. Accordingly, the maximum efficiency of the lifting mechanism per its operation cycle was obtained. Also, the optimal gear ratio ensures the minimum dimensions of a multi-threaded two-stage gearbox.KeywordsGear RatioMoment of InertiaDynamic LoadsProduct Innovation
This paper presents a mathematical model of an electric power system which consists of a three-phase power line with distributed parameters and an equivalent, unbalanced RLC load cooperating with the line. The above model was developed on the basis of the modified Hamilton–Ostrogradsky principle, which extends the classical Lagrangian by adding two more components: the energy of dissipative forces in the system and the work of external non-conservative forces. In the developed model, there are four types of energy and four types of linear energy density. On the basis of Hamilton’s principle, the extended action functional was formulated and then minimized. As a result, the extremal of the action functional was derived, which can be treated as a solution of the Euler–Lagrange equation for the subsystem with lumped parameters and the Euler–Poisson equation for the subsystem with distributed parameters. The derived system of differential equations describes the entire physical system and consists of ordinary differential equations and partial differential equations. Such a system can be regarded as a full mathematical model of a dynamic object based on interdisciplinary approaches. The partial derivatives in the derived differential state–space equations of the analyzed object are approximated by means of finite differences, and then these equations are integrated in the time coordinate using the Runge–Kutta method of the fourth order. The results of computer simulation of transient processes in the dynamic system are presented as graphs and then discussed.
