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• W3196874102 abstract "The problems of accurate measurement of the forces transmitted to the rotating shafts of electric motors have been solved for more than one century. At the same time, they have not lost their relevance, which is due to the wide development and variety of electric motors and power plants, the specific operating conditions of which require the use of a wide arsenal of measuring instruments. An important aspect in the process of using high-precision electric motors in such areas as medicine, vehicles, military-industrial complex is the improvement of the metrological characteristics of measuring equipment. In such conditions, power measurements at high-speed installations, where in some cases conventional measurement systems are either unsuitable or have low accuracy, are of particular importance. At the same time, in the absence of means of accurate determination of the error, attempts are made to predict them, which makes it possible to determine the influence of subtle factors on the efficiency of power plants. Even under optimal conditions for the functioning of measuring instruments, due to the influence of a number of factors, gross errors may appear. Such errors are unpredictable, and their significance is difficult to predict. To prevent the impact of negative factors on the operation of measuring instruments, additional sensors are often used, for example, to identify unnecessary vibrations, vibrometers are used in parallel with strain gauges. In the absence of such additional measuring sensors, in order to identify gross errors in diagnosing the characteristics of the moment of force, it is advisable to use machine learning tools, factor analysis techniques, simulation modeling, and other forecasting tools. With the help of such methods, among the sampling of data obtained from strain gauges, or other sensors, for measuring the moment of force, it is possible to identify deviations from normal operation, through certain frequency patterns of such influences. Among the many works describing the characteristics of errors in measuring physical quantities, there are not many that are devoted to predicting the accuracy of measuring sensors. Thus, when the measured conditions change, gross errors occur that negate the process of controlling electric motors, which is often the cause of an emergency condition. To solve this problem, you need simple and affordable tools that will allow you to form a classification of deviations in measurement errors. However, taking into account a significant number of factors of influence on the measuring medium, this can be realized only under the condition of an individual approach to the construction of measuring instruments. For this purpose, a stand was developed for measuring the metrological characteristics of electric motors. It was tested in conditions of increased vibration. The results of such tests made it possible to determine the deviations from the nominal error value of the strain gauge sensor.And also highlight a number of features of such a deviation caused by the frequency characteristics of the pulse source. The structure of the software and technical characteristics of the proposed stand and its comparison with existing analogs, as well as the functional and electrical circuit are presented. As a result of testing the proposed stand, a classification of factors influencing the accuracy of strain gauges was developed." @default.
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• W3196874102 date "2021-08-27" @default.
• W3196874102 modified "2023-09-27" @default.
• W3196874102 title "Розробка стенду для вимірювання метрологічних характеристик електродвигунів" @default.
• W3196874102 doi "https://doi.org/10.32620/aktt.2021.4sup2.14" @default.
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