Synchronization of Measurement Data with the Reference System

Abstract

Abstract Today, most devices are equipped with sensors that enable the collection of process data that influences the control parameters. Sensors are to replace human senses and provide information from the environment to the control algorithm. In many cases, the sensors used are subject to reference measurements from an external diagnostic system, which is to eliminate possible errors in the installation of sensors or the operation of the control algorithm. For this purpose, external systems are most often used that do not duplicate any errors from the sensors used. Most often these are vision systems that are based on the measurement of markers mounted on the tested object. The most important effect of the reference system is the verification of sensor data or the correction of the control algorithm that processes sensor data. Often, when comparing two measurement systems, there is a problem with unequal sampling rates. The main problem is comparing the two graphs as the number of data / arguments is different. In order to compare two graphs, many methods are used to reduce or extend the number of arguments. The use of data expansion or reduction methods may result in an additional error. In this article, methods of reducing measurement data from IMU sensors and encoders connected to servo motors will be presented. There is a significant difference in sampling time for the two measurement systems shown. At the beginning, the methods and applications of algorithms in the literature will be discussed. Then, the measurement data will be compared with the data processed by the algorithms. The final point of work will be the combination of the data processed by the algorithm with the measurements. Two measurements were also compared in order to estimate the measurement error and a comparative algorithm was proposed.