AUTOMATED SYSTEM FOR DIAGNOSING INTERNAL SURFACES OF INDUSTRIAL AUTOCLAVES USING A SPHERICAL PARALLEL MECHANISM

Abstract

The article is devoted to the solution of the actual problem of increasing the efficiency and reliability of diagnostics of the internal surfaces of industrial autoclaves, which are used in many branches. Traditional control methods are often laborious, subjective and do not always provide complete coverage, which necessitates the development of automated diagnostic systems. The purpose of the study is to develop an automated system for diagnosing the internal surfaces of industrial autoclaves using a spherical parallel mechanism (SPM). The SPM, due to its kinematics structure, provides high maneuverability and orientation of the diagnostic tool in a wide range of angles, which is important for examining complex geometric shapes of autoclaves. Existing methods of automated scanning and trajectory planning are analyzed, in particular methods based on geometric models and path search algorithms (A*, RRT). Strategies for scanning the internal surfaces of autoclaves, such as linear, spiral, circular, zigzag and square scanning, are considered, taking into account the shape of the autoclave, sensor characteristics and diagnostic purpose. To implement trajectories for scanning the inner surface of the autoclave, avoiding obstacles or focusing on certain areas, it is proposed to use the solution of the inverse kinematics problem to determine the required positions of the drives at each step of the movement. The results of modeling the SPM movement along typical trajectories (spiral, circle, zigzag, square) are presented. The structure of an automated system has been developed, which includes an operator interface, a central controller, SPM trajectory planning and motion control modules, a sensor control system, a SPM drive control unit, a data collection and pre-processing system, the SPM itself, a diagnostic tool (sensor), a data analysis and interpretation system, as well as a data storage, archiving and report generation system. The developed automated system demonstrates flexibility and adaptability to different types and sizes of industrial autoclaves and provides increased efficiency, speed and objectivity of monitoring the condition of their inner surfaces. The prospect of further research is the development of effective methods for data analysis and evaluation of defect parameters.