Acoustic Diagnostics of Lever Mechanisms with Subsequent Processing of Data on Neural Networks

Abstract

The technique of acoustic diagnostics for machine tools -robots is developed. A neural network reference model has been constructed that allows to diagnose the current characteristics of the state of objects under different conditions, namely, the configuration of the mechanism, the geometric parameters of the mechanism with the motor-spindle running, the dynamics of the movement of the nodes of the experimental stand mechanism with variable speed and load on the drive, and the temperature of the object. Experiments have been carried out to investigate the relationship between the parameters of the spectrum of an acoustic signal with a given discreteness, excited by a perturbing effect in the form of "white noise." The possibility of using the proposed approach to the management of complex technological machines, such as machines with mechanisms based on parallel kinematics, is shown to improve the accuracy of the positioning of the actuators, to ensure their dynamic tuning and to optimize the trajectories of the movements of the working organs of the equipment.

Simulation of operation of neural network with purpose of utilisation of hydraulic actuators in complicated technical conditions

“…Therefore, it is not surprising that the growing interest in this technology has led to a significant expansion of the scope of its application, the emergence of a multitude of different approaches, training algorithms, software products, application options. Specific features and main difficulties were considered in respect of their utilisation in the problems, which differ from the problems, which are considered as classical problems for their solving with the help of the neural networks [2] . Prospects of such an approach are determined by timeliness, applicability and cost effectiveness of the focused attention, investigation in this direction [3] .…”