Метод визначення вібраційних характеристик промислового обладнання в частотній та часовій областях

Abstract

This paper proposes hardware and software solutions and a data processing method for vibration diagnostics of industrial equipment, which uses discrete Fourier transform and Allan dispersion to increase the accuracy and stability of measurement processes and result processing. The object of this study is the use of vibration diagnostic methods to implement the concept of maintenance of industrial equipment based on monitoring its current and future condition. The subject of this research is the hardware and software solutions for vibration diagnostics systems and methods for processing measurement results. The purpose of this work is to develop a new resource-saving IoT-oriented wireless solution for vibration diagnostics, where the contact method and MEMS accelerometers are used to measure vibration parameters and to evaluate the effectiveness of new methods and algorithms for processing experimental data. The task: justify the need to find new hardware and software solutions and methods of processing the obtained results for the implementation of the service concept based on the tracking of vibration indicators of technical equipment; provide basic hardware and software solutions for the implementation of the cloud platform of vibration diagnostics; develop methods of processing results; check the developed methods and algorithms using mathematical modeling methods and in an on-site experiment; compare the effectiveness of own and competitive solutions; draw conclusions and formulate a plan for further research. Conclusions. It has been proven that the combination of known analysis methods in the time and frequency domains with multi-level processing gives better results than analogous methods. The developed hardware and software tools and the method of processing measurement results effectively implement the contact method of vibration measurement, which provides the possibility of tracking the state of technical equipment. The developed equipment for the calibration of vibration acceleration sensors can reduce accelerometer errors. Further areas of research are the search for the optimal distribution of calculations on IoT levels, reducing the computational complexity of algorithms, increasing the time of continuous autonomous operation of the lower-level microcontroller, creating micro services for time-series analysis, and researching the dependence of the technical state of the equipment on the calculated Allan deviation.